hexsha string | size int64 | ext string | lang string | max_stars_repo_path string | max_stars_repo_name string | max_stars_repo_head_hexsha string | max_stars_repo_licenses list | max_stars_count int64 | max_stars_repo_stars_event_min_datetime string | max_stars_repo_stars_event_max_datetime string | max_issues_repo_path string | max_issues_repo_name string | max_issues_repo_head_hexsha string | max_issues_repo_licenses list | max_issues_count int64 | max_issues_repo_issues_event_min_datetime string | max_issues_repo_issues_event_max_datetime string | max_forks_repo_path string | max_forks_repo_name string | max_forks_repo_head_hexsha string | max_forks_repo_licenses list | max_forks_count int64 | max_forks_repo_forks_event_min_datetime string | max_forks_repo_forks_event_max_datetime string | content string | avg_line_length float64 | max_line_length int64 | alphanum_fraction float64 | qsc_code_num_words_quality_signal int64 | qsc_code_num_chars_quality_signal float64 | qsc_code_mean_word_length_quality_signal float64 | qsc_code_frac_words_unique_quality_signal float64 | qsc_code_frac_chars_top_2grams_quality_signal float64 | qsc_code_frac_chars_top_3grams_quality_signal float64 | qsc_code_frac_chars_top_4grams_quality_signal float64 | qsc_code_frac_chars_dupe_5grams_quality_signal float64 | qsc_code_frac_chars_dupe_6grams_quality_signal float64 | qsc_code_frac_chars_dupe_7grams_quality_signal float64 | qsc_code_frac_chars_dupe_8grams_quality_signal float64 | qsc_code_frac_chars_dupe_9grams_quality_signal float64 | qsc_code_frac_chars_dupe_10grams_quality_signal float64 | qsc_code_frac_chars_replacement_symbols_quality_signal float64 | qsc_code_frac_chars_digital_quality_signal float64 | qsc_code_frac_chars_whitespace_quality_signal float64 | qsc_code_size_file_byte_quality_signal float64 | qsc_code_num_lines_quality_signal float64 | qsc_code_num_chars_line_max_quality_signal float64 | qsc_code_num_chars_line_mean_quality_signal float64 | qsc_code_frac_chars_alphabet_quality_signal float64 | qsc_code_frac_chars_comments_quality_signal float64 | qsc_code_cate_xml_start_quality_signal float64 | qsc_code_frac_lines_dupe_lines_quality_signal float64 | qsc_code_cate_autogen_quality_signal float64 | qsc_code_frac_lines_long_string_quality_signal float64 | qsc_code_frac_chars_string_length_quality_signal float64 | qsc_code_frac_chars_long_word_length_quality_signal float64 | qsc_code_frac_lines_string_concat_quality_signal float64 | qsc_code_cate_encoded_data_quality_signal float64 | qsc_code_frac_chars_hex_words_quality_signal float64 | qsc_code_frac_lines_prompt_comments_quality_signal float64 | qsc_code_frac_lines_assert_quality_signal float64 | qsc_codepython_cate_ast_quality_signal float64 | qsc_codepython_frac_lines_func_ratio_quality_signal float64 | qsc_codepython_cate_var_zero_quality_signal bool | qsc_codepython_frac_lines_pass_quality_signal float64 | qsc_codepython_frac_lines_import_quality_signal float64 | qsc_codepython_frac_lines_simplefunc_quality_signal float64 | qsc_codepython_score_lines_no_logic_quality_signal float64 | qsc_codepython_frac_lines_print_quality_signal float64 | qsc_code_num_words int64 | qsc_code_num_chars int64 | qsc_code_mean_word_length int64 | qsc_code_frac_words_unique null | qsc_code_frac_chars_top_2grams int64 | qsc_code_frac_chars_top_3grams int64 | qsc_code_frac_chars_top_4grams int64 | qsc_code_frac_chars_dupe_5grams int64 | qsc_code_frac_chars_dupe_6grams int64 | qsc_code_frac_chars_dupe_7grams int64 | qsc_code_frac_chars_dupe_8grams int64 | qsc_code_frac_chars_dupe_9grams int64 | qsc_code_frac_chars_dupe_10grams int64 | qsc_code_frac_chars_replacement_symbols int64 | qsc_code_frac_chars_digital int64 | qsc_code_frac_chars_whitespace int64 | qsc_code_size_file_byte int64 | qsc_code_num_lines int64 | qsc_code_num_chars_line_max int64 | qsc_code_num_chars_line_mean int64 | qsc_code_frac_chars_alphabet int64 | qsc_code_frac_chars_comments int64 | qsc_code_cate_xml_start int64 | qsc_code_frac_lines_dupe_lines int64 | qsc_code_cate_autogen int64 | qsc_code_frac_lines_long_string int64 | qsc_code_frac_chars_string_length int64 | qsc_code_frac_chars_long_word_length int64 | qsc_code_frac_lines_string_concat null | qsc_code_cate_encoded_data int64 | qsc_code_frac_chars_hex_words int64 | qsc_code_frac_lines_prompt_comments int64 | qsc_code_frac_lines_assert int64 | qsc_codepython_cate_ast int64 | qsc_codepython_frac_lines_func_ratio int64 | qsc_codepython_cate_var_zero int64 | qsc_codepython_frac_lines_pass int64 | qsc_codepython_frac_lines_import int64 | qsc_codepython_frac_lines_simplefunc int64 | qsc_codepython_score_lines_no_logic int64 | qsc_codepython_frac_lines_print int64 | effective string | hits int64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
97678f96eb58a15cf993ddeb3a83d03e026f412c | 1,035 | py | Python | nfv/nfv-vim/nfv_vim/tables/_system_table.py | SidneyAn/nfv | 5f0262a5b6ea4be59f977b9c587c483cbe0e373d | [
"Apache-2.0"
] | 2 | 2020-02-07T19:01:36.000Z | 2022-02-23T01:41:46.000Z | nfv/nfv-vim/nfv_vim/tables/_system_table.py | SidneyAn/nfv | 5f0262a5b6ea4be59f977b9c587c483cbe0e373d | [
"Apache-2.0"
] | 1 | 2021-01-14T12:02:25.000Z | 2021-01-14T12:02:25.000Z | nfv/nfv-vim/nfv_vim/tables/_system_table.py | SidneyAn/nfv | 5f0262a5b6ea4be59f977b9c587c483cbe0e373d | [
"Apache-2.0"
] | 2 | 2021-01-13T08:39:21.000Z | 2022-02-09T00:21:55.000Z | #
# Copyright (c) 2015-2016 Wind River Systems, Inc.
#
# SPDX-License-Identifier: Apache-2.0
#
from nfv_vim import database
from nfv_vim.tables._table import Table
_system_table = None
class SystemTable(Table):
"""
System Table
"""
def __init__(self):
super(SystemTable, self).__init__()
def _persist_value(self, value):
database.database_system_add(value)
def _unpersist_value(self, key):
database.database_system_delete(key)
def tables_get_system_table():
"""
Get the system table
"""
return _system_table
def system_table_initialize():
"""
Initialize the system table
"""
global _system_table
_system_table = SystemTable()
_system_table.persist = False
systems = database.database_system_get_list()
for system in systems:
_system_table[system.name] = system
_system_table.persist = True
def system_table_finalize():
"""
Finalize the system table
"""
global _system_table
del _system_table
| 18.482143 | 50 | 0.681159 | 124 | 1,035 | 5.306452 | 0.387097 | 0.267477 | 0.072948 | 0.06079 | 0.094225 | 0.094225 | 0 | 0 | 0 | 0 | 0 | 0.012531 | 0.228986 | 1,035 | 55 | 51 | 18.818182 | 0.81203 | 0.16715 | 0 | 0.086957 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.26087 | false | 0 | 0.086957 | 0 | 0.434783 | 0 | 0 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
976b9e3b867f145ea3e26423273854ab636a3e4a | 439 | py | Python | cs_131b/0_week/absolutely_nothing.py | kimberleejohnson/python-study | 5dc08007a1bc18c91e32879a0e9d5cad1bd1cdd3 | [
"MIT"
] | null | null | null | cs_131b/0_week/absolutely_nothing.py | kimberleejohnson/python-study | 5dc08007a1bc18c91e32879a0e9d5cad1bd1cdd3 | [
"MIT"
] | null | null | null | cs_131b/0_week/absolutely_nothing.py | kimberleejohnson/python-study | 5dc08007a1bc18c91e32879a0e9d5cad1bd1cdd3 | [
"MIT"
] | null | null | null | # This is a comment!
'''
This isn't technically a comment,
but no program can execute between the quotes,
and it's fun!
'''
"""
Same goes here!
"""
# I am so excited for everything we will learn in this course.
# 🐍🐍🐍🐍🐍🐍🐍🐍🐍🐍🐍
# To any of my fellow peers reading this, have you heard of pyLadies?
# There's a Slack channel and a former meetup group in SF.
# It doesn't look like much is happening now, but study groups would be great! | 29.266667 | 79 | 0.694761 | 78 | 439 | 4.051282 | 0.807692 | 0.050633 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.205011 | 439 | 15 | 79 | 29.266667 | 0.873926 | 0.897494 | 0 | null | 0 | null | 0 | 0 | null | 0 | 0 | 0 | null | 1 | null | true | 0 | 0 | null | null | null | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
976c2348978bef6fa8d0df120008584e26b09a77 | 147 | py | Python | model/Cart.py | crippledfaith/shop | fb6a520170968e9f90d4d70c3f6a4e793b105e84 | [
"Apache-2.0"
] | null | null | null | model/Cart.py | crippledfaith/shop | fb6a520170968e9f90d4d70c3f6a4e793b105e84 | [
"Apache-2.0"
] | null | null | null | model/Cart.py | crippledfaith/shop | fb6a520170968e9f90d4d70c3f6a4e793b105e84 | [
"Apache-2.0"
] | null | null | null | from model.BaseModel import BaseModel
class Cart(BaseModel):
def __init__(self):
super().__init__()
self.sale_id = ""
| 13.363636 | 37 | 0.612245 | 16 | 147 | 5.0625 | 0.75 | 0.197531 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.278912 | 147 | 10 | 38 | 14.7 | 0.764151 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.2 | false | 0 | 0.2 | 0 | 0.6 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2 |
9776f381f2c7798d4b5d09f824b6a26772926a6e | 670 | py | Python | python_codes/rot13.py | RudranshPratapSingh/my-other-codes | a6450820fd20d0700aee310af00bafb959534de2 | [
"MIT"
] | 1 | 2020-12-02T04:01:34.000Z | 2020-12-02T04:01:34.000Z | python_codes/rot13.py | RudranshPratapSingh/my-other-codes | a6450820fd20d0700aee310af00bafb959534de2 | [
"MIT"
] | null | null | null | python_codes/rot13.py | RudranshPratapSingh/my-other-codes | a6450820fd20d0700aee310af00bafb959534de2 | [
"MIT"
] | null | null | null | # coded in python3
# video :
text = input("Enter your text : ")
check = True
etext = ""
for chars in text:
if(ord(chars)) <= 90 and ord(chars) <= 65:
if((ord(chars) + 13) > 90):
x = 64 + ((ord(chars) + 13) - 90)
else:
x = ord(chars) + 13
elif(ord(chars) <= 122 and ord(chars) >= 97):
if (ord(chars) + 13 > 122):
x = 96 + ((ord(chars) + 13) - 122)
else:
x = ord(chars) + 13
elif(ord(chars) == 32):
x = 32
else:
check = False
break
etext = str(etext) + chr(x)
if(check == False):
print("Invalid Characters found")
else:
print(etext)
| 23.103448 | 49 | 0.474627 | 89 | 670 | 3.573034 | 0.393258 | 0.27673 | 0.188679 | 0.075472 | 0.169811 | 0.169811 | 0.169811 | 0.169811 | 0 | 0 | 0 | 0.093458 | 0.361194 | 670 | 28 | 50 | 23.928571 | 0.649533 | 0.038806 | 0 | 0.25 | 0 | 0 | 0.065728 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.083333 | 0 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
97838cc2b02b373e081b58cb4a569d120be2e4d5 | 563 | py | Python | src/utilities/calibrator/pic16f15356_device_information_area.py | pete-restall/Cluck2Sesame | 4a2e749d3e94178fb96501d92d3008cae0a07005 | [
"MIT"
] | 2 | 2016-10-04T05:13:22.000Z | 2017-11-18T12:07:31.000Z | src/utilities/calibrator/pic16f15356_device_information_area.py | pete-restall/Cluck2Sesame | 4a2e749d3e94178fb96501d92d3008cae0a07005 | [
"MIT"
] | null | null | null | src/utilities/calibrator/pic16f15356_device_information_area.py | pete-restall/Cluck2Sesame | 4a2e749d3e94178fb96501d92d3008cae0a07005 | [
"MIT"
] | null | null | null | class Pic16f15356DeviceInformationArea:
def __init__(self, address, dia):
if len(dia) != 32:
raise ValueError('dia', f'PIC16F15356 DIA is 32 words but received {len(dia)} words')
self._address = address
self._raw = dia.copy()
self._device_id = ''.join(['{:04x}'.format(id_byte) for id_byte in dia[0x00:0x09]])
self._fvra2x = dia[0x19]
@property
def address(self): return self._address
@property
def raw(self): return self._raw.copy()
@property
def device_id(self): return self._device_id
@property
def fvra2x(self): return self._fvra2x
| 25.590909 | 88 | 0.715808 | 82 | 563 | 4.707317 | 0.414634 | 0.11399 | 0.145078 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.066806 | 0.149201 | 563 | 21 | 89 | 26.809524 | 0.73904 | 0 | 0 | 0.25 | 0 | 0 | 0.117229 | 0 | 0 | 0 | 0.021314 | 0 | 0 | 1 | 0.3125 | false | 0 | 0 | 0.25 | 0.375 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 2 |
9785df24cb1e33cbd743f136da97162effcf2bc0 | 5,409 | py | Python | tomso/utils.py | warrickball/tomso | 842c4287a827c252ef0b25f443370ab71900c77a | [
"MIT"
] | 3 | 2018-09-26T10:32:46.000Z | 2021-07-16T09:59:55.000Z | tomso/utils.py | warrickball/tomso | 842c4287a827c252ef0b25f443370ab71900c77a | [
"MIT"
] | 2 | 2018-09-26T11:32:46.000Z | 2020-12-11T13:13:37.000Z | tomso/utils.py | warrickball/tomso | 842c4287a827c252ef0b25f443370ab71900c77a | [
"MIT"
] | 2 | 2018-12-11T14:32:49.000Z | 2021-04-07T06:03:01.000Z | """Utility functions used by other modules."""
import numpy as np
import gzip
from .constants import sigma_SB
from .constants import GMsun, Rsun, Dnu_sun # adiabatic
from .constants import Lsun, nu_max_sun, Teff_sun # full
def integrate(y, x):
"""Integral of `y` over `x`, computed using the trapezoidal rule.
i.e. :math:`\\int _{x[0]} ^x y(x') dx'`."""
dz = 0.5*(y[1:]+y[:-1])*np.diff(x)
return np.hstack((0., np.cumsum(dz)))
def complement(y, x):
"""Complement of integral of `y` over `x`, computed using the
trapezoidal rule. i.e. :math:`\\int _x^{x[-1]}y(x') dx'`."""
z = integrate(y, x)
return z[-1] - z
def regularize(y0=0.0, x0=1e-12):
def regularizer(f):
def regularized_f(s):
with np.errstate(divide='ignore', invalid='ignore'):
y = f(s)
y[s.x < x0] = y0
return y
return regularized_f
return regularizer
def tomso_open(filename, *args, **kwargs):
"""Wrapper function to open files ending with `.gz` with built-in
`gzip` module or paths starting with `http` using
`urllib.request.urlopen`, otherwise use normal open. `.gz` and
normal modes take the same arguments as `open` and `gzip.open` and
return a file object."""
if filename.startswith('http'):
from urllib.request import urlopen
return urlopen(filename)
elif filename.lower().endswith('.gz'):
return gzip.open(filename, *args, **kwargs)
else:
return open(filename, *args, **kwargs)
def load_mesa_gyre(filename, mesa_or_gyre):
"""Most MESA and GYRE output files both adhere to a similar columned
ASCII format, so it makes more sense to have one implementation
for reading them, rather than re-implementing it in each
submodule.
"""
with tomso_open(filename, 'rb') as f:
lines = f.readlines()
if mesa_or_gyre == 'mesa':
header = np.genfromtxt(lines[1:3], names=True, dtype=None, encoding='utf-8')
elif mesa_or_gyre == 'gyre':
# the GYRE header might be empty
try:
header = np.genfromtxt(lines[2:4], names=True, dtype=None, encoding='utf-8')
except IndexError:
header = None
else:
raise ValueError("mesa_or_gyre must be either 'mesa' or 'gyre', not %s"
% mesa_or_gyre)
data = np.genfromtxt(lines[5:], names=True, dtype=None, encoding='utf-8')
return header, data
def get_Teff(L, R):
"""Determine the effective temperature `Teff` for a given luminosity
`L` and radius `R`, both in cgs units."""
return (L/(4.*np.pi*R**2*sigma_SB))**0.25
class AdiabaticStellarModel(object):
"""Base stellar model class that defines properties that are computed
the same way in all stellar model formats for which only adiabatic
frequencies can be calculated."""
def __str__(self):
return '\n'.join([
'%s' % type(self),
'M %9.3e g %7.3f Msun' % (self.M, self.G*self.M/GMsun),
'R %9.3e cm %8.3f Rsun' % (self.R, self.R/Rsun),
'Dnu %9.1f uHz %7.3f Dnu_sun' % (self.Dnu, self.Dnu_factor)
])
@property
def Dnu_factor(self):
return (self.G*self.M/GMsun/self.R**3*Rsun**3)**0.5
@property
def Dnu(self): return self.Dnu_factor*Dnu_sun
@property
@regularize()
def g(self): return self.G*self.m/self.r**2
@property
def dP_dr(self): return -self.rho*self.g
@property
@regularize(y0=np.inf)
def Hp(self): return -self.P/self.dP_dr
@property
@regularize()
def drho_dr(self): return -self.rho*(1/self.Gamma_1/self.Hp + self.AA/self.r)
@property
@regularize(y0=np.inf)
def Hrho(self): return -self.rho/self.drho_dr
@property
def n_eff(self): return 1/(self.Hrho/self.Hp-1)
@property
def cs2(self): return self.Gamma_1*self.P/self.rho
@property
def cs(self): return self.cs2**0.5
@property
def N(self):
y = np.full(len(self.x), 0.)
y[self.N2>0] = self.N2[self.N2>0]**0.5
return y
@property
@regularize(y0=np.inf)
def S2_1(self): return 2.*self.cs2/self.r**2
@property
def S_1(self): return self.S2_1**0.5
class FullStellarModel(AdiabaticStellarModel):
"""Base stellar model class that defines properties that are computed
the same way in all stellar model formats for which both adiabatic
and non-adiabatic frequencies can be calculated."""
def __str__(self):
return super(FullStellarModel, self).__str__() + '\n' + \
'\n'.join([
'L %9.3e erg/s %8.3f Lsun' % (self.L, self.L/Lsun),
'Teff %7i K %7.3f Teff_sun' % (self.Teff, self.Teff/Teff_sun),
'nu_max %7i uHz %7.3f nu_max_sun' % (self.nu_max, self.nu_max_factor)])
@property
def Teff(self): return get_Teff(self.L, self.R)
@property
def nu_max_factor(self):
return self.G*self.M/GMsun/(self.R/Rsun)**2/(self.Teff/Teff_sun)**0.5
@property
def nu_max(self):
return self.nu_max_factor*nu_max_sun
@property
def Gamma_2(self): return 1.0/(1.0-self.grad_a)
@property
def Gamma_3(self): return 1. + (1.-1./self.Gamma_2)*self.Gamma_1
@property
def grad_r(self): return 3*self.kappa*self.P*self.L_r/(64.*np.pi*sigma_SB*self.G*self.m*self.T**4)
| 30.559322 | 102 | 0.614716 | 834 | 5,409 | 3.894484 | 0.278177 | 0.061576 | 0.051724 | 0.015394 | 0.248153 | 0.20936 | 0.17734 | 0.149631 | 0.149631 | 0.118227 | 0 | 0.025698 | 0.244592 | 5,409 | 176 | 103 | 30.732955 | 0.769212 | 0.226474 | 0 | 0.275229 | 0 | 0 | 0.069414 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.266055 | false | 0 | 0.055046 | 0.183486 | 0.486239 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 2 |
97b695eeabd0994b6733d3b9ec23a25579ed1382 | 896 | py | Python | viper/cli.py | curtisma/conda-virtuoso | 46c07341432d36436a6a59358ad364b7240b6015 | [
"MIT"
] | 2 | 2021-09-19T02:56:04.000Z | 2022-03-09T07:30:58.000Z | viper/cli.py | curtisma/conda-virtuoso | 46c07341432d36436a6a59358ad364b7240b6015 | [
"MIT"
] | 13 | 2021-09-16T05:17:51.000Z | 2022-01-25T07:36:08.000Z | viper/cli.py | curtisma/conda-virtuoso | 46c07341432d36436a6a59358ad364b7240b6015 | [
"MIT"
] | null | null | null | """
Command line interface for viper
"""
import click
from .docs import docs as docs_internal
from .cdslib import add_library, include_cdslib
@click.group()
def virt():
"""
Cadence virtuoso command-line utilities
"""
pass
@virt.command()
def docs():
docs_internal()
@virt.group()
def cdslib():
"""Edit a *.cdslib file"""
pass
@cdslib.command()
@click.argument("cds_path")
@click.argument("library_name")
@click.argument("library_path")
def add():
"""
Add a library
"""
add_library(cds_path, library_name, library_path)
@cdslib.command()
@click.argument("cds_path")
@click.argument("include_file_path")
@click.option('-s','--soft')
def include():
"""
Include another cds.lib file in the current one.
:return:
"""
include_cdslib(cds_path, include_file_path, soft)
if __name__ == '__main__':
virt(auto_envvar_prefix='VIRT')
| 18.666667 | 53 | 0.672991 | 116 | 896 | 4.956897 | 0.37931 | 0.113043 | 0.062609 | 0.090435 | 0.16 | 0.16 | 0.16 | 0.16 | 0 | 0 | 0 | 0 | 0.174107 | 896 | 47 | 54 | 19.06383 | 0.777027 | 0.184152 | 0 | 0.230769 | 0 | 0 | 0.115097 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.192308 | true | 0.076923 | 0.115385 | 0 | 0.307692 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 2 |
97cb288a655f8069b49f38cc90b8e4f6f76f7c17 | 5,523 | py | Python | fastinference/models/nn/Activations.py | njru8cjo/fastinference | a3ea755eb91ea386f4c23a7ed4ddbc4e7a180ade | [
"MIT"
] | 11 | 2021-10-04T14:58:42.000Z | 2022-02-24T14:52:11.000Z | fastinference/models/nn/Activations.py | njru8cjo/fastinference | a3ea755eb91ea386f4c23a7ed4ddbc4e7a180ade | [
"MIT"
] | 1 | 2022-02-17T12:49:38.000Z | 2022-02-17T12:49:38.000Z | fastinference/models/nn/Activations.py | njru8cjo/fastinference | a3ea755eb91ea386f4c23a7ed4ddbc4e7a180ade | [
"MIT"
] | 5 | 2021-11-03T03:02:07.000Z | 2022-02-27T01:21:58.000Z | import numpy as np
from .Layer import Layer
class Sign():
"""Sign Layer
f(x) = 1 for x > 0
f(x) = 0 for x = 0
f(x) = -1 for x < 0
Attributes:
input_shape = [N, C, H, W]: The shape of the input tensor
output_shape = [N, C, H, W]: The shape of the resulting output tensor, must match the input shape
"""
def __init__(self, graph, node, input_shape):
super().__init__(input_shape, input_shape, "sign")
# self.input_shape = get_tensor_shape(graph, node.output[0])
# self.output_shape = input_shape
# self.name = "sign"
class Sigmoid(Layer):
"""Sigmoid activation
f(x) = 1 / (1 + exp(-x))
Attributes:
input_shape = [N, C, H, W]: The shape of the input tensor
output_shape = [N, C, H, W]: The shape of the resulting output tensor, must match the input shape
"""
def __init__(self, graph, node, input_shape):
super().__init__(input_shape, input_shape, "sigmoid")
class Relu(Layer):
"""Rectified Linear Unit
f(x) = max(0, x)
Attributes:
input_shape = [N, C, H, W]: The shape of the input tensor
output_shape = [N, C, H, W]: The shape of the resulting output tensor, must match the input shape
"""
def __init__(self, graph, node, input_shape):
super().__init__(input_shape, input_shape, "relu")
class LeakyRelu(Layer):
"""Leaky Rectified Linear Unit
f(x) = alpha * x for x < 0
f(x) = x for x >= 0
Attributes:
input_shape = [N, C, H, W]: The shape of the input tensor
output_shape = [N, C, H, W]: The shape of the resulting output tensor, must match the input shape
alpha: Coefficient of leakage
"""
def __init__(self, graph, node, input_shape):
super().__init__(input_shape, input_shape, "leakyrelu")
class Step(Layer):
"""Step Layer
f(x) = high for x > threshold
f(x) = high for x = threshold and threshold_is_high
f(x) = low for x = threshold and not threshold_is_high
f(x) = low for x < threshold
This is the Activation Layer in a binary neural net as it has only two distinct outputs (in comparison
to the three outputs of Sign Layers). There is no official support for Step Layers in ONNX.
To generate a net with Step Layers, use the following ONNX structure:
Greater + Where or
Less + Where
The code generator will convert this into a Step Layer if the binary argument is passed.
Example in PyTorch:
x = torch.where(x > 0, torch.tensor([1.0]), torch.tensor([-1.0]))
When a BatchNormalization Layer follows directly afterwards, the scales and biases are embedded as thresholds
of the Step Layer. The following holds since x is an integer:
x * s - b > 0
x > int(b / s)
The output is directly packed into ints of size binary_word_size. This is done by setting each bit individually.
The following sets the c'th leftmost bit to 1 or 0:
output |= (1U << ((binary_word_size-1) - c % binary_word_size))
output &= ~(1U << ((binary_word_size-1) - c % binary_word_size))
Attributes:
input_shape = [N, C, H, W]: The shape of the input tensor
output_shape = [N, C, H, W]: The shape of the resulting output tensor, must match the input shape
threshold: The threshold, can be scalar or numpy array
low: Value selected at indices where x < threshold
high: Value selected at indices where x > threshold
threshold_is_high: Whether high value is selected where x = threshold
"""
def __init__(self, input_shape, threshold, low, high):
super().__init__(input_shape, input_shape, "step")
self.threshold = threshold
self.low = low
self.high = high
self.threshold_is_high = True
# class Softmax(Layer):
# """Softmax (normalized exponential)
# To combat numerical issues when doing softmax computation, a common trick is used that shifts
# the input vector by subtracting the maximum element in it from all elements.
# z = x - max(x)
# numerator = np.exp(z)
# denominator = np.sum(numerator)
# softmax = numerator/denominator
# Attributes:
# output_shape = [N, D]: The dimension of the output tensor
# """
# def __init__(self, output_shape):
# self.input_shape = self.output_shape = output_shape
# def render(self, backend, **kwargs):
# code_init = ''
# code_alloc = super(Softmax, self).render('alloc', output_shape=self.output_shape, backend=backend, **kwargs)
# code_predict = super(Softmax, self).render('softmax', output_size=self.output_shape[1], backend=backend,**kwargs)
# return code_init, code_alloc, code_predict
# def output_type(self, input_type, backend):
# return 'float'
class LogSoftmax(Layer):
"""Log of Softmax
To combat numerical issues when doing softmax computation, a common trick is used that shifts
the input vector by subtracting the maximum element in it from all elements.
z = x - max(x)
numerator = np.exp(z)
denominator = np.sum(numerator)
softmax = numerator/denominator
logsoftmax = np.log(softmax)
Attributes:
output_shape = [N, D]: The dimension of the output tensor
"""
def __init__(self, graph, node, input_shape):
super().__init__(input_shape, input_shape, "logsoftmax") | 35.403846 | 123 | 0.637335 | 785 | 5,523 | 4.329936 | 0.219108 | 0.091203 | 0.020594 | 0.023536 | 0.53604 | 0.511621 | 0.488673 | 0.466902 | 0.466902 | 0.447485 | 0 | 0.006176 | 0.267065 | 5,523 | 156 | 124 | 35.403846 | 0.833498 | 0.751584 | 0 | 0.208333 | 0 | 0 | 0.035647 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0 | 0.083333 | 0 | 0.583333 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2 |
97cc8129b5e0eaedc29f0145925261bdd49ee464 | 741 | py | Python | runtests.py | vasantharajr/AirMapSDK-Embedded | a1cc41bad46d9dfba98d7d01e04cb54a38987bf8 | [
"Apache-2.0"
] | 7 | 2016-10-20T17:50:40.000Z | 2021-11-28T00:44:39.000Z | runtests.py | vasantharajr/AirMapSDK-Embedded | a1cc41bad46d9dfba98d7d01e04cb54a38987bf8 | [
"Apache-2.0"
] | 1 | 2017-01-31T19:40:35.000Z | 2017-01-31T19:40:35.000Z | runtests.py | isabella232/AirMapSDK-Embedded | a1cc41bad46d9dfba98d7d01e04cb54a38987bf8 | [
"Apache-2.0"
] | 3 | 2016-12-03T00:17:59.000Z | 2021-03-26T12:17:58.000Z | from test.unit import test_access, test_statusapi, test_createflightapi, test_telemetryapi
import sys
testFail = 0
ret = test_access.test_start()
if ret == 1:
print "Access Test Failed..."
testFail = 1
else:
print "Pass: Access Test"
ret = test_statusapi.test_start()
if ret == 1:
print "Status Test Failed..."
testFail = 1
else:
print "Pass: Status Test"
ret = test_createflightapi.test_start()
if ret == 1:
print "Create Flight Test Failed..."
testFail = 1
else:
print "Pass: Create Flight Test"
ret = test_telemetryapi.test_start()
if ret == 1:
print "Telemetry Test Failed..."
testFail = 1
else:
print "Pass: Telemetry Test"
if testFail == 0:
print "Final: **All Tests Passed**"
else:
print "Final: **Test Failed**"
| 19 | 90 | 0.708502 | 107 | 741 | 4.794393 | 0.252336 | 0.097466 | 0.08577 | 0.109162 | 0.405458 | 0.405458 | 0.249513 | 0 | 0 | 0 | 0 | 0.016234 | 0.168691 | 741 | 38 | 91 | 19.5 | 0.816558 | 0 | 0 | 0.419355 | 0 | 0 | 0.298246 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0.16129 | 0.064516 | null | null | 0.322581 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 |
97ce18707b7c76857b00671bd45426129aeabac5 | 5,118 | py | Python | pyplex/glfw/contants.py | pyplex/pyplex | 66e19acb3efd1a8a69d28022edcb0b6ad5cb6b11 | [
"MIT"
] | 5 | 2018-01-17T09:08:38.000Z | 2020-09-20T20:38:51.000Z | pyplex/glfw/contants.py | pyplex/pyplex | 66e19acb3efd1a8a69d28022edcb0b6ad5cb6b11 | [
"MIT"
] | null | null | null | pyplex/glfw/contants.py | pyplex/pyplex | 66e19acb3efd1a8a69d28022edcb0b6ad5cb6b11 | [
"MIT"
] | null | null | null | import enum
VERSION_MAJOR = 3
VERSION_MINOR = 2
VERSION_REVISION = 1
FOCUSED = 0x00020001
ICONIFIED = 0x00020002
RESIZABLE = 0x00020003
VISIBLE = 0x00020004
DECORATED = 0x00020005
AUTO_ICONIFY = 0x00020006
FLOATING = 0x00020007
MAXIMIZED = 0x00020008
RED_BITS = 0x00021001
GREEN_BITS = 0x00021002
BLUE_BITS = 0x00021003
ALPHA_BITS = 0x00021004
DEPTH_BITS = 0x00021005
STENCIL_BITS = 0x00021006
ACCUM_RED_BITS = 0x00021007
ACCUM_GREEN_BITS = 0x00021008
ACCUM_BLUE_BITS = 0x00021009
ACCUM_ALPHA_BITS = 0x0002100A
AUX_BUFFERS = 0x0002100B
STEREO = 0x0002100C
SAMPLES = 0x0002100D
SRGB_CAPABLE = 0x0002100E
REFRESH_RATE = 0x0002100F
DOUBLEBUFFER = 0x00021010
CLIENT_API = 0x00022001
CONTEXT_VERSION_MAJOR = 0x00022002
CONTEXT_VERSION_MINOR = 0x00022003
CONTEXT_REVISION = 0x00022004
CONTEXT_ROBUSTNESS = 0x00022005
OPENGL_FORWARD_COMPAT = 0x00022006
OPENGL_DEBUG_CONTEXT = 0x00022007
OPENGL_PROFILE = 0x00022008
CONTEXT_RELEASE_BEHAVIOR = 0x00022009
CONTEXT_NO_ERROR = 0x0002200A
CONTEXT_CREATION_API = 0x0002200B
NO_API = 0
OPENGL_API = 0x00030001
OPENGL_ES_API = 0x00030002
NO_ROBUSTNESS = 0
NO_RESET_NOTIFICATION = 0x00031001
LOSE_CONTEXT_ON_RESET = 0x00031002
OPENGL_ANY_PROFILE = 0
OPENGL_CORE_PROFILE = 0x00032001
OPENGL_COMPAT_PROFILE = 0x00032002
CURSOR = 0x00033001
STICKY_KEYS = 0x00033002
STICKY_MOUSE_BUTTONS = 0x00033003
ANY_RELEASE_BEHAVIOR = 0
RELEASE_BEHAVIOR_FLUSH = 0x00035001
RELEASE_BEHAVIOR_NONE = 0x00035002
NATIVE_CONTEXT_API = 0x00036001
EGL_CONTEXT_API = 0x00036002
CONNECTED = 0x00040001
DISCONNECTED = 0x00040002
DONT_CARE = -1
class PrettyPrintIntEnum(enum.IntEnum):
def __format__(self, format_spec):
return self.__str__()
class PrettyPrintIntFlag(enum.IntFlag):
def __format__(self, format_spec):
return self.__str__()
class Key(PrettyPrintIntEnum):
UNKNOWN = -1
SPACE = 32
APOSTROPHE = 39
COMMA = 44
MINUS = 45
PERIOD = 46
SLASH = 47
D0 = 48
D1 = 49
D2 = 50
D3 = 51
D4 = 52
D5 = 53
D6 = 54
D7 = 55
D8 = 56
D9 = 57
SEMICOLON = 59
EQUAL = 61
A = 65
B = 66
C = 67
D = 68
E = 69
F = 70
G = 71
H = 72
I = 73
J = 74
K = 75
L = 76
M = 77
N = 78
O = 79
P = 80
Q = 81
R = 82
S = 83
T = 84
U = 85
V = 86
W = 87
X = 88
Y = 89
Z = 90
LEFT_BRACKET = 91
BACKSLASH = 92
RIGHT_BRACKET = 93
GRAVE_ACCENT = 96
WORLD_1 = 161
WORLD_2 = 162
ESCAPE = 256
ENTER = 257
TAB = 258
BACKSPACE = 259
INSERT = 260
DELETE = 261
RIGHT = 262
LEFT = 263
DOWN = 264
UP = 265
PAGE_UP = 266
PAGE_DOWN = 267
HOME = 268
END = 269
CAPS_LOCK = 280
SCROLL_LOCK = 281
NUM_LOCK = 282
PRINT_SCREEN = 283
PAUSE = 284
F1 = 290
F2 = 291
F3 = 292
F4 = 293
F5 = 294
F6 = 295
F7 = 296
F8 = 297
F9 = 298
F10 = 299
F11 = 300
F12 = 301
F13 = 302
F14 = 303
F15 = 304
F16 = 305
F17 = 306
F18 = 307
F19 = 308
F20 = 309
F21 = 310
F22 = 311
F23 = 312
F24 = 313
F25 = 314
KP_0 = 320
KP_1 = 321
KP_2 = 322
KP_3 = 323
KP_4 = 324
KP_5 = 325
KP_6 = 326
KP_7 = 327
KP_8 = 328
KP_9 = 329
KP_DECIMAL = 330
KP_DIVIDE = 331
KP_MULTIPLY = 332
KP_SUBTRACT = 333
KP_ADD = 334
KP_ENTER = 335
KP_EQUAL = 336
LEFT_SHIFT = 340
LEFT_CONTROL = 341
LEFT_ALT = 342
LEFT_SUPER = 343
RIGHT_SHIFT = 344
RIGHT_CONTROL = 345
RIGHT_ALT = 346
RIGHT_SUPER = 347
MENU = 348
class Button(PrettyPrintIntEnum):
B1 = 0
B2 = 1
B3 = 2
B4 = 3
B5 = 4
B6 = 5
B7 = 6
B8 = 7
LEFT = B1
RIGHT = B2
MIDDLE = B3
class Joystick(PrettyPrintIntEnum):
JOYSTICK_1 = 0
JOYSTICK_2 = 1
JOYSTICK_3 = 2
JOYSTICK_4 = 3
JOYSTICK_5 = 4
JOYSTICK_6 = 5
JOYSTICK_7 = 6
JOYSTICK_8 = 7
JOYSTICK_9 = 8
JOYSTICK_10 = 9
JOYSTICK_11 = 10
JOYSTICK_12 = 11
JOYSTICK_13 = 12
JOYSTICK_14 = 13
JOYSTICK_15 = 14
JOYSTICK_16 = 15
class Action(PrettyPrintIntEnum):
RELEASE = 0
PRESS = 1
REPEAT = 2
class Modifiers(PrettyPrintIntFlag):
SHIFT = 0x0001
CONTROL = 0x0002
ALT = 0x0004
SUPER = 0x0008
class ConnectionEvent(PrettyPrintIntFlag):
CONNECTED = 0x00040001
DISCONNECTED = 0x00040002
class CursorMode(PrettyPrintIntFlag):
NORMAL = 0x00034001
HIDDEN = 0x00034002
DISABLED = 0x00034003
class CursorShape(PrettyPrintIntFlag):
ARROW = 0x00036001
IBEAM = 0x00036002
CROSSHAIR = 0x00036003
HAND = 0x00036004
HRESIZE = 0x00036005
VRESIZE = 0x00036006
class Error(enum.IntEnum):
NOT_INITIALIZED = 0x00010001
NO_CURRENT_CONTEXT = 0x00010002
INVALID_ENUM = 0x00010003
INVALID_VALUE = 0x00010004
OUT_OF_MEMORY = 0x00010005
API_UNAVAILABLE = 0x00010006
VERSION_UNAVAILABLE = 0x00010007
PLATFORM_ERROR = 0x00010008
FORMAT_UNAVAILABLE = 0x00010009
NO_WINDOW_CONTEXT = 0x0001000A | 18.543478 | 42 | 0.652403 | 656 | 5,118 | 4.858232 | 0.655488 | 0.018826 | 0.019454 | 0.02573 | 0.02573 | 0.02573 | 0.02573 | 0.02573 | 0.02573 | 0 | 0 | 0.303724 | 0.291716 | 5,118 | 276 | 43 | 18.543478 | 0.575448 | 0 | 0 | 0.032 | 0 | 0 | 0 | 0 | 0 | 0 | 0.143387 | 0 | 0 | 1 | 0.008 | false | 0 | 0.004 | 0.008 | 0.768 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2 |
8ad91da038614971fd2f8a054486756b08f7d8a4 | 51 | py | Python | travy/example_config.py | ribal-aladeeb/Simple-Camera | a4d664b0878e8e86e126c45fb0df9f5aa62ce5b3 | [
"Apache-2.0"
] | null | null | null | travy/example_config.py | ribal-aladeeb/Simple-Camera | a4d664b0878e8e86e126c45fb0df9f5aa62ce5b3 | [
"Apache-2.0"
] | 2 | 2019-01-11T17:06:29.000Z | 2019-01-19T04:05:56.000Z | travy/example_config.py | YannCedric/Simple-Camera | a4d664b0878e8e86e126c45fb0df9f5aa62ce5b3 | [
"Apache-2.0"
] | 2 | 2020-01-16T07:21:51.000Z | 2020-03-19T20:41:48.000Z | #rename file to config.py
token = "YOUR TOKEN HERE" | 25.5 | 25 | 0.745098 | 9 | 51 | 4.222222 | 0.888889 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.156863 | 51 | 2 | 26 | 25.5 | 0.883721 | 0.470588 | 0 | 0 | 0 | 0 | 0.555556 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
8ae046390839602a6171d49a813ea57477f3cfde | 5,329 | py | Python | plums/dataflow/io/tile/_format/ptype.py | alexandreMayerowitz/playground-plums | a6be79e4c30c7abcbade5581f052a4e8035a2057 | [
"MIT"
] | null | null | null | plums/dataflow/io/tile/_format/ptype.py | alexandreMayerowitz/playground-plums | a6be79e4c30c7abcbade5581f052a4e8035a2057 | [
"MIT"
] | null | null | null | plums/dataflow/io/tile/_format/ptype.py | alexandreMayerowitz/playground-plums | a6be79e4c30c7abcbade5581f052a4e8035a2057 | [
"MIT"
] | 2 | 2021-02-03T12:37:53.000Z | 2022-03-09T03:48:12.000Z | try:
from functools import lru_cache
except ImportError:
from backports.functools_lru_cache import lru_cache
from .utils import ConversionFunction
from .channels import channels_register, Channel
class ptype(object): # noqa: N801
"""The *pixel-type* of a given image: A representation of its spectral base.
As each actual pixel are stored as vectors, understanding of the base used is compulsory to decode a given pixel
vector, the *pixel-type* class describes the way a given pixel is stored as a vector of *channel* values
(e.g. *RGB*, *BGR*, *HSL*, *XYZ* etc...).
Args:
string (str): A string description of the *pixel-type* as a list of channel characters (*e.g.* ``'RGB'``,
``'rgY'``, ``'bgr'``, ``'y'``...).
"""
def __init__(self, string):
self._channels = tuple(channels_register[item]() for item in string)
def __repr__(self):
"""Return a pythonic representation or a *pixel-type*."""
return 'ptype(\'{}\')'.format(''.join(channel.__short_name__ for channel in self._channels))
def __str__(self):
"""Return a human readable representation or a *pixel-type*."""
return ''.join(channel.__short_name__ for channel in self._channels)
def __hash__(self):
"""Compute the *pixel-type* python hash as the has of its |Channel| vector."""
return hash(self._channels)
def __getitem__(self, index):
"""Get the i-th |Channel| from the *pixel-type* |Channel| vector."""
return self._channels[index]
def __len__(self):
"""Get the dimension number of the |Channel| space of the *pixel-type*."""
return len(self._channels)
def __eq__(self, other):
"""Return whether 2 |ptype| instances have the same |Channel| vector, thus describing the same *pixel-type*."""
try:
return self._channels == tuple(channel for channel in other)
except TypeError:
return NotImplemented
def __ne__(self, other):
"""Return whether 2 |ptype| do not have the same |Channel| vector, thus not describing the same *pixel-type*."""
return not self == other
@staticmethod
def _find_secondary_in_primary(secondary_list, primary_list):
len_primary, len_secondary = len(primary_list), len(secondary_list)
i, last = 0, len_primary - len_secondary + 1
while True:
try:
found = primary_list.index(secondary_list[0], i, last) # find first elem in secondary_list
except ValueError:
return None
if primary_list[found:found + len_secondary] == secondary_list:
return found, found + len_secondary
else:
i = found + 1
def __contains__(self, channels):
"""Return whether the *pixel-type* |Channel| vector contains a given |Channel| or |Channel| "sub-vector"."""
return self.slice(channels) is not None
def contains(self, channels):
"""Return whether the *pixel-type* |Channel| vector contains a given |Channel| or |Channel| "sub-set"."""
return self.index(channels) is not None
def slice(self, channels):
"""Compute the *pixel-type* |channel| vector slice of a given sub-vector.
Args:
channels (tuple, |Channel|): Either a single |Channel| or a tuple of |Channel| assumed to be a sub-vector of
the *pixel-type* |Channel| vector.
Returns:
(int, int) or ``None``: The slice of the |Channel| vector corresponding to the input or ``None`` if it is
not contained in the |Channel| vector.
"""
if isinstance(channels, Channel):
channels = channels,
return self._find_secondary_in_primary(channels, self._channels)
def index(self, channels):
"""Compute the *pixel-type* |channel| indices of a given sub-set.
Args:
channels (tuple, |Channel|): Either a single |Channel| or a tuple of |Channel| assumed to be a sub-set of
the *pixel-type* |Channel| vector.
Returns:
(int, ) or ``None``: The indices of the |Channel| corresponding to the input or ``None`` if it is
not contained in the |Channel| vector.
"""
if isinstance(channels, Channel):
channels = channels,
try:
return tuple(self._channels.index(channel) for channel in channels)
except ValueError:
return None
@lru_cache(maxsize=10)
def get_conversion_fn_to(self, destination_ptype):
"""Compute the conversion function from self to another ptype.
Args:
destination_ptype (|ptype|): The destination ptype object.
Returns:
callable: A conversion function to move from one ptype to another.
"""
return ConversionFunction(self, destination_ptype)
RGB = rgb = ptype('RGB') # Pixel stored as *Red*-*Green*-*Blue* channels.
RGBA = rgba = ptype('RGBA') # Pixel stored as *Red*-*Green*-*Blue*-*Alpha* channels.
BGR = bgr = ptype('BGR') # Pixel stored as *Blue*-*Green*-*Red* channels.
BGRA = bgra = ptype('BGRA') # Pixel stored as *Blue*-*Green*-*Red*-*Alpha* channels.
GREY = grey = Y = y = ptype('Y') # Pixel stored as a single *Grey* channels.
| 40.067669 | 120 | 0.628823 | 681 | 5,329 | 4.787078 | 0.226138 | 0.044172 | 0.044172 | 0.040798 | 0.366871 | 0.330061 | 0.245399 | 0.222086 | 0.199387 | 0.199387 | 0 | 0.002787 | 0.259336 | 5,329 | 132 | 121 | 40.371212 | 0.823157 | 0.469694 | 0 | 0.193548 | 0 | 0 | 0.008963 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.225806 | false | 0 | 0.080645 | 0 | 0.580645 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2 |
8af05789cab384fef209cd7272c9b4bd7e1541b0 | 405 | py | Python | moderator/tests/models.py | mpyatishev/djmoderator | 0d532bef4b40cecbcc297f0cda1dc0aeba3d676c | [
"MIT"
] | null | null | null | moderator/tests/models.py | mpyatishev/djmoderator | 0d532bef4b40cecbcc297f0cda1dc0aeba3d676c | [
"MIT"
] | null | null | null | moderator/tests/models.py | mpyatishev/djmoderator | 0d532bef4b40cecbcc297f0cda1dc0aeba3d676c | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
from django.db import models
class Model(models.Model):
name = models.CharField(max_length=255)
class ModelFK(models.Model):
name = models.CharField(max_length=255)
parent = models.ForeignKey(Model, related_name="modelfk")
class ModelM2M(models.Model):
name = models.CharField(max_length=255)
first = models.ManyToManyField(Model, related_name='second')
| 22.5 | 64 | 0.723457 | 52 | 405 | 5.538462 | 0.442308 | 0.114583 | 0.15625 | 0.21875 | 0.4375 | 0.4375 | 0.4375 | 0.4375 | 0 | 0 | 0 | 0.031792 | 0.145679 | 405 | 17 | 65 | 23.823529 | 0.800578 | 0.051852 | 0 | 0.333333 | 0 | 0 | 0.034031 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.111111 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2 |
8af362a9d5b5f087b21f2756bc9ebb0e15db2f6a | 1,585 | py | Python | pypertrail/saved_searches.py | astrolox/pypertrail | 9cd8dd64821433487ea93e0eb3ce6b54f79fc237 | [
"MIT"
] | 15 | 2016-10-06T22:55:19.000Z | 2020-12-04T09:52:32.000Z | pypertrail/saved_searches.py | kwent/pypertrail | 9cd8dd64821433487ea93e0eb3ce6b54f79fc237 | [
"MIT"
] | 2 | 2017-08-04T09:04:08.000Z | 2020-11-21T09:26:03.000Z | pypertrail/saved_searches.py | astrolox/pypertrail | 9cd8dd64821433487ea93e0eb3ce6b54f79fc237 | [
"MIT"
] | 3 | 2018-10-05T22:11:26.000Z | 2020-02-20T01:55:30.000Z | from .api import API
import requests
class SavedSearch(API):
def list(self):
r = requests.get('{0}/{1}'.format(self.base_uri, 'searches.json'),
headers=self.headers)
return self.return_response(r)
def show(self, saved_search_id):
r = requests.get('{0}/{1}/{2}{3}'.format(self.base_uri,
'searches', saved_search_id,
'.json'),
headers=self.headers)
return self.return_response(r)
def create(self, payload=None):
r = requests.post('{0}/{1}'.format(self.base_uri, 'searches.json'),
headers=self.headers,
params=payload)
return self.return_response(r)
def update(self, saved_search_id, payload=None):
r = requests.put('{0}/{1}/{2}{3}'.format(self.base_uri,
'searches', saved_search_id,
'.json'),
headers=self.headers,
params=payload)
return self.return_response(r)
def delete(self, saved_search_id):
r = requests.delete('{0}/{1}/{2}{3}'.format(self.base_uri,
'searches',
saved_search_id,
'.json'),
headers=self.headers)
return self.return_response(r)
| 39.625 | 77 | 0.440379 | 151 | 1,585 | 4.476821 | 0.231788 | 0.097633 | 0.115385 | 0.12574 | 0.769231 | 0.747041 | 0.670118 | 0.670118 | 0.670118 | 0.670118 | 0 | 0.018182 | 0.444795 | 1,585 | 39 | 78 | 40.641026 | 0.75 | 0 | 0 | 0.53125 | 0 | 0 | 0.076341 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.15625 | false | 0 | 0.0625 | 0 | 0.40625 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
8afb55d9b72e76faf06d7107b5fd25871691e390 | 361 | py | Python | emit_main/test/conftest.py | emit-sds/emit-main | 7c2f6feacc68b8a962309d8a3a7f6decc571c69d | [
"Apache-2.0"
] | 1 | 2022-02-11T17:05:52.000Z | 2022-02-11T17:05:52.000Z | emit_main/test/conftest.py | emit-sds/emit-main | 7c2f6feacc68b8a962309d8a3a7f6decc571c69d | [
"Apache-2.0"
] | null | null | null | emit_main/test/conftest.py | emit-sds/emit-main | 7c2f6feacc68b8a962309d8a3a7f6decc571c69d | [
"Apache-2.0"
] | null | null | null | """
This config file allows pytest to pass arguments into tests
Author: Winston Olson-Duvall, winston.olson-duvall@jpl.nasa.gov
"""
from pytest import fixture
def pytest_addoption(parser):
parser.addoption(
"--config_path",
action="store"
)
@fixture()
def config_path(request):
return request.config.getoption("--config_path")
| 18.05 | 63 | 0.703601 | 45 | 361 | 5.555556 | 0.644444 | 0.12 | 0.144 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.180055 | 361 | 19 | 64 | 19 | 0.844595 | 0.34349 | 0 | 0 | 0 | 0 | 0.135371 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.222222 | false | 0 | 0.111111 | 0.111111 | 0.444444 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 2 |
8affa5bc2b45b6bbaa5c1c822b1c498984fb7bdb | 167 | py | Python | python/048-self-powers.py | timschlechter/project-euler | 8986863231cc2d7d6ad1922c5009b96d329712e4 | [
"MIT"
] | null | null | null | python/048-self-powers.py | timschlechter/project-euler | 8986863231cc2d7d6ad1922c5009b96d329712e4 | [
"MIT"
] | null | null | null | python/048-self-powers.py | timschlechter/project-euler | 8986863231cc2d7d6ad1922c5009b96d329712e4 | [
"MIT"
] | null | null | null | from functools import reduce
powers = map(lambda x: x**x, range(1, 1001))
summation = reduce(lambda x, y: x + y, powers)
last10 = str(summation)[-10:]
print(last10)
| 20.875 | 46 | 0.688623 | 27 | 167 | 4.259259 | 0.62963 | 0.121739 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.078014 | 0.155689 | 167 | 7 | 47 | 23.857143 | 0.737589 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.2 | 0 | 0.2 | 0.2 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
c10b65d1af2890255ceb7a5bef994f69a9db3798 | 506 | py | Python | qqbot/model/announce.py | wzpan/botpy | 3c112d2f429342bf0d3480dbf3fb6677aa2b486a | [
"MIT"
] | 1 | 2022-03-30T13:04:32.000Z | 2022-03-30T13:04:32.000Z | qqbot/model/announce.py | wzpan/botpy | 3c112d2f429342bf0d3480dbf3fb6677aa2b486a | [
"MIT"
] | null | null | null | qqbot/model/announce.py | wzpan/botpy | 3c112d2f429342bf0d3480dbf3fb6677aa2b486a | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
class Announce:
def __init__(self, data=None):
self.guild_id: str = ""
self.channel_id: str = ""
self.message_id: str = ""
if data:
self.__dict__ = data
class CreateAnnounceRequest:
def __init__(self, channel_id: str, message_id: str):
self.channel_id = channel_id
self.message_id = message_id
class CreateChannelAnnounceRequest:
def __init__(self, message_id: str):
self.message_id = message_id
| 23 | 57 | 0.626482 | 61 | 506 | 4.737705 | 0.311475 | 0.217993 | 0.124567 | 0.110727 | 0.349481 | 0 | 0 | 0 | 0 | 0 | 0 | 0.002703 | 0.268775 | 506 | 21 | 58 | 24.095238 | 0.778378 | 0.041502 | 0 | 0.142857 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.214286 | false | 0 | 0 | 0 | 0.428571 | 0 | 0 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
c119ef903768815c911ddf123ea3ce4c3bf04181 | 342 | py | Python | 实例学习Numpy与Matplotlib/matplotlib入门例子.py | shao1chuan/pythonbook | cd9877d04e1e11422d38cc051e368d3d9ce2ab45 | [
"MulanPSL-1.0"
] | 95 | 2020-10-11T04:45:46.000Z | 2022-02-25T01:50:40.000Z | 实例学习Numpy与Matplotlib/matplotlib入门例子.py | shao1chuan/pythonbook | cd9877d04e1e11422d38cc051e368d3d9ce2ab45 | [
"MulanPSL-1.0"
] | null | null | null | 实例学习Numpy与Matplotlib/matplotlib入门例子.py | shao1chuan/pythonbook | cd9877d04e1e11422d38cc051e368d3d9ce2ab45 | [
"MulanPSL-1.0"
] | 30 | 2020-11-05T09:01:00.000Z | 2022-03-08T05:58:55.000Z |
import matplotlib.pyplot as plt
import numpy as np
x = np.linspace(0, 2 * np.pi, 50)
y = np.sin(x)
# plt.plot(x, y)
# plt.show()
# plt.plot(x, y)
# plt.plot(x, y * 2)
# plt.title("sin(x) & 2sin(x)")
# plt.show()
plt.plot(x, y, label="sin(x)")
plt.plot(x, y * 2, label="2sin(x)")
# plt.legend()
plt.legend(loc='best bbbbbbbbbb')
plt.show() | 18 | 35 | 0.605263 | 68 | 342 | 3.044118 | 0.352941 | 0.169082 | 0.193237 | 0.217391 | 0.333333 | 0.280193 | 0 | 0 | 0 | 0 | 0 | 0.027682 | 0.154971 | 342 | 19 | 36 | 18 | 0.688581 | 0.330409 | 0 | 0 | 0 | 0 | 0.126697 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.25 | 0 | 0.25 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
c12ef57dd5ed6fb1b549eb6c8d6d0eb7da4bd9e4 | 447 | py | Python | chargebee/models/site_migration_detail.py | koordinates/chargebee-python | 8c3e8309484cc45375e5585ff931696da94ac2fa | [
"MIT"
] | 28 | 2015-09-16T01:52:44.000Z | 2022-01-13T21:38:55.000Z | chargebee/models/site_migration_detail.py | koordinates/chargebee-python | 8c3e8309484cc45375e5585ff931696da94ac2fa | [
"MIT"
] | 45 | 2015-01-22T15:41:23.000Z | 2022-03-31T11:12:49.000Z | chargebee/models/site_migration_detail.py | koordinates/chargebee-python | 8c3e8309484cc45375e5585ff931696da94ac2fa | [
"MIT"
] | 23 | 2017-01-10T15:41:48.000Z | 2022-03-21T14:16:54.000Z | import json
from chargebee.model import Model
from chargebee import request
from chargebee import APIError
class SiteMigrationDetail(Model):
fields = ["entity_id", "other_site_name", "entity_id_at_other_site", "migrated_at", "entity_type", \
"status"]
@staticmethod
def list(params=None, env=None, headers=None):
return request.send_list_request('get', request.uri_path("site_migration_details"), params, env, headers)
| 29.8 | 113 | 0.749441 | 58 | 447 | 5.534483 | 0.568966 | 0.121495 | 0.11838 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.143177 | 447 | 14 | 114 | 31.928571 | 0.83812 | 0 | 0 | 0 | 0 | 0 | 0.223714 | 0.100671 | 0 | 0 | 0 | 0 | 0 | 1 | 0.1 | false | 0 | 0.4 | 0.1 | 0.8 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 2 |
c13e884682ceee597e7c082102bcfe5b1fd9d33c | 389 | py | Python | code/backend/tests/test_products.py | ndhngoc91/COMP90082_S1_TO_2021 | 91cc5d039df3b4d271b100a9afec99897a9501a2 | [
"MIT"
] | 2 | 2021-08-22T05:10:27.000Z | 2021-11-08T12:57:27.000Z | code/backend/tests/test_products.py | ndhngoc91/COMP90082_S1_TO_2021 | 91cc5d039df3b4d271b100a9afec99897a9501a2 | [
"MIT"
] | null | null | null | code/backend/tests/test_products.py | ndhngoc91/COMP90082_S1_TO_2021 | 91cc5d039df3b4d271b100a9afec99897a9501a2 | [
"MIT"
] | 1 | 2021-08-21T19:51:33.000Z | 2021-08-21T19:51:33.000Z | # implement test cases for the Product router
import pytest
import json
@pytest.fixture(autouse=True, scope="function")
def run_around_tests():
setup()
yield
teardown()
def setup():
pass
def teardown():
pass
def test_get_all_products(test_app):
response = test_app.get("/products")
assert response.status_code == 200
assert len(response.json()) > 0
| 15.56 | 47 | 0.691517 | 52 | 389 | 5.019231 | 0.653846 | 0.05364 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.012862 | 0.200514 | 389 | 24 | 48 | 16.208333 | 0.826367 | 0.11054 | 0 | 0.133333 | 0 | 0 | 0.049419 | 0 | 0 | 0 | 0 | 0 | 0.133333 | 1 | 0.266667 | false | 0.133333 | 0.133333 | 0 | 0.4 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 |
c13f566bd7155be4b712fd3326b7f1dde6216e4f | 465 | py | Python | django_factories/other_class_factories.py | danie1k/django-factories | fe21a30a9b09f4d5a69312ad912fd5ac989faed0 | [
"BSD-3-Clause"
] | null | null | null | django_factories/other_class_factories.py | danie1k/django-factories | fe21a30a9b09f4d5a69312ad912fd5ac989faed0 | [
"BSD-3-Clause"
] | null | null | null | django_factories/other_class_factories.py | danie1k/django-factories | fe21a30a9b09f4d5a69312ad912fd5ac989faed0 | [
"BSD-3-Clause"
] | null | null | null | __all__ = ['class_in_class_factory']
def class_in_class_factory(parent_class, name, bases=None, **fields):
if not (isinstance(bases, tuple) or bases is None):
raise TypeError('`bases` must be tuple.')
fields['__module__'] = '{parent_class_module_name}.{parent_class_name}'.format(
parent_class_module_name=parent_class.__module__,
parent_class_name=parent_class.__name__,
)
return type(name, bases or (object, ), fields)
| 33.214286 | 83 | 0.713978 | 61 | 465 | 4.868852 | 0.409836 | 0.259259 | 0.20202 | 0.127946 | 0.215488 | 0.215488 | 0 | 0 | 0 | 0 | 0 | 0 | 0.167742 | 465 | 13 | 84 | 35.769231 | 0.767442 | 0 | 0 | 0 | 0 | 0 | 0.215054 | 0.146237 | 0 | 0 | 0 | 0 | 0 | 1 | 0.111111 | false | 0 | 0 | 0 | 0.222222 | 0 | 0 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
c15c8e84a39e3f4ebb21798135a4f6dce8fb337d | 3,086 | py | Python | test_password_meter.py | Layto888/password-meter-py | a865a05ec5e78b1a239dcd77215c1825e7a32199 | [
"MIT"
] | 5 | 2017-07-02T19:36:32.000Z | 2021-06-06T11:21:34.000Z | test_password_meter.py | Layto888/password-meter-py | a865a05ec5e78b1a239dcd77215c1825e7a32199 | [
"MIT"
] | 1 | 2019-10-21T17:11:58.000Z | 2021-06-01T22:41:55.000Z | test_password_meter.py | Layto888/password-meter-py | a865a05ec5e78b1a239dcd77215c1825e7a32199 | [
"MIT"
] | null | null | null | import pytest
from password_meter import Password
from constants import ALL, USE_LETTERS, USE_DIGITS, USE_PUNCTATIONS
# set up fixture
@pytest.fixture(scope='module')
def password():
pswd = Password(':abcdX01J!b#')
yield pswd
def test_attributes(password):
assert isinstance(password, Password)
assert isinstance(password.password, str)
assert password.len == 12
assert password.nupper == 2
assert password.nlower == 5
assert password.ndigit == 2
assert password.symbol == 3
assert password.requirement == 5
def test_middle_ns(password):
assert password._middle_ns() / 2 == 3
def test_only_letters(password):
assert password._only_letters() == 0
def test_only_digits(password):
assert password._only_digits() == 0
def test_consecutive_letter(password):
assert password._consecutive_letter() / -2 == 3
def test_consecutive_digit(password):
assert password._consecutive_digit() / -2 == 1
def test_check_sequential(password):
assert password._check_sequential() / -3 == 2
def test_global_score(password):
password._global_score()
assert password.score >= 100.0
# test specifications types
def test_random_password_spec(password):
assert ALL == USE_LETTERS + USE_DIGITS + USE_PUNCTATIONS
# new find safe password test with cases:
passwd, score = Password().find(8, spec=USE_DIGITS)
assert len(passwd) == 8
s_digits = sum(c.isdigit() for c in passwd)
assert s_digits == 8
passwd, score = Password().find(8, spec=USE_LETTERS)
s_letters = sum(c.isalpha() for c in passwd)
assert s_letters == 8
assert score > 5.0 and score < 100.0
# test special cases password
def test_specials_cases_password():
special_pass = Password('')
assert special_pass.len == 0
assert special_pass.nupper == 0
assert special_pass.nlower == 0
assert special_pass.ndigit == 0
assert special_pass.symbol == 0
assert special_pass.requirement == 0
# score compute part A and B
special_pass._compute_addition()
assert special_pass.score == 0
special_pass._compute_deduction()
assert special_pass.score == 0
special_pass._global_score()
assert special_pass.score == 0
# only digits
special_pass = Password('0123456789')
assert special_pass._only_digits() == -10.0
assert special_pass._consecutive_digit() == -18.0
assert special_pass._check_sequential() == -24.0
# only letters
special_pass = Password('ABCDefcbAARk')
assert special_pass._only_letters() == - 12.0
assert special_pass._consecutive_letter() == -20.0
assert special_pass._check_sequential() == -6.0
def test_repetitive_chars2():
""" test complexe function _repetitive_chars2 """
passwd = Password('axbxcxdxexfx')
assert passwd._repetitive_chars2() == 0
passwd = Password('abbbbb01b')
assert passwd._repetitive_chars2() == -16
passwd = Password('000000013xbv11')
assert passwd._repetitive_chars2() == -37
passwd = Password('Oharrrrrrrrrrrrrrrrg!')
assert passwd._repetitive_chars2() == -100
| 28.841121 | 67 | 0.710629 | 394 | 3,086 | 5.314721 | 0.236041 | 0.110315 | 0.121777 | 0.077364 | 0.219198 | 0.146132 | 0.096466 | 0 | 0 | 0 | 0 | 0.038599 | 0.185677 | 3,086 | 106 | 68 | 29.113208 | 0.794668 | 0.066105 | 0 | 0.041667 | 0 | 0 | 0.033461 | 0.00732 | 0 | 0 | 0 | 0 | 0.541667 | 1 | 0.166667 | false | 0.875 | 0.041667 | 0 | 0.208333 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 |
c162f5d2f814fc86c8bb6ad6c9ab6906cdcc8455 | 408 | py | Python | lymph/testing/nose2.py | MislavStipetic/lymph | aa36a688380e5665fdea31fda76b4a0cf35b6fc0 | [
"Apache-2.0"
] | 89 | 2015-03-01T11:39:55.000Z | 2022-01-31T22:00:15.000Z | lymph/testing/nose2.py | MislavStipetic/lymph | aa36a688380e5665fdea31fda76b4a0cf35b6fc0 | [
"Apache-2.0"
] | 214 | 2015-01-02T23:48:49.000Z | 2020-01-14T10:47:37.000Z | lymph/testing/nose2.py | MislavStipetic/lymph | aa36a688380e5665fdea31fda76b4a0cf35b6fc0 | [
"Apache-2.0"
] | 36 | 2015-01-13T13:44:15.000Z | 2021-09-15T17:55:41.000Z | from __future__ import absolute_import
import logging
from nose2.events import Plugin
log = logging.getLogger('nose2.plugins.lymph')
class LymphPlugin(Plugin):
"""
Initializes the lymph framework before tests are run
"""
configSection = 'lymph'
def createTests(self, event):
log.info("Initializing lymph framework")
import lymph.monkey
lymph.monkey.patch()
| 19.428571 | 56 | 0.698529 | 46 | 408 | 6.086957 | 0.652174 | 0.1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00625 | 0.215686 | 408 | 20 | 57 | 20.4 | 0.86875 | 0.127451 | 0 | 0 | 0 | 0 | 0.152941 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.1 | false | 0 | 0.4 | 0 | 0.7 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 2 |
c16c27384446f91c7a7df4aa03b9a4a28419dde0 | 280 | py | Python | NumberGuesser.py | MaxHartel/NumberGuesser | 0abe8c6fa19bd2b7f910c7934a0e0b847094feeb | [
"MIT"
] | null | null | null | NumberGuesser.py | MaxHartel/NumberGuesser | 0abe8c6fa19bd2b7f910c7934a0e0b847094feeb | [
"MIT"
] | null | null | null | NumberGuesser.py | MaxHartel/NumberGuesser | 0abe8c6fa19bd2b7f910c7934a0e0b847094feeb | [
"MIT"
] | null | null | null | import random
rand = random.randint(0,100)
while True:
inputX = input("Enter a number")
inputX = int(inputX)
if(inputX > rand):
print("Too High")
if(inputX < rand):
print("Too Low")
if(inputX == rand):
print("Good Job")
break;
| 20 | 36 | 0.557143 | 36 | 280 | 4.333333 | 0.611111 | 0.153846 | 0.230769 | 0.326923 | 0.25641 | 0 | 0 | 0 | 0 | 0 | 0 | 0.020408 | 0.3 | 280 | 13 | 37 | 21.538462 | 0.77551 | 0 | 0 | 0 | 0 | 0 | 0.132616 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.083333 | 0 | 0.083333 | 0.25 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
c16eb1ddb129becd8565a11fa0ff9c975ba59fc3 | 357 | py | Python | pytpp/attributes/log_filter.py | Venafi/pytpp | 42af655b2403b8c9447c86962abd4aaa0201f646 | [
"MIT"
] | 4 | 2022-02-04T23:58:55.000Z | 2022-02-15T18:53:08.000Z | pytpp/attributes/log_filter.py | Venafi/pytpp | 42af655b2403b8c9447c86962abd4aaa0201f646 | [
"MIT"
] | null | null | null | pytpp/attributes/log_filter.py | Venafi/pytpp | 42af655b2403b8c9447c86962abd4aaa0201f646 | [
"MIT"
] | null | null | null | from pytpp.attributes._helper import IterableMeta, Attribute
from pytpp.attributes.log_channel import LogChannelAttributes
class LogFilterAttributes(LogChannelAttributes, metaclass=IterableMeta):
__config_class__ = "Log Filter"
filter_ids = Attribute('Filter IDs')
filter_severity = Attribute('Filter Severity')
log_channel = Attribute('Log Channel')
| 35.7 | 72 | 0.826331 | 38 | 357 | 7.5 | 0.447368 | 0.105263 | 0.133333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.095238 | 357 | 9 | 73 | 39.666667 | 0.882353 | 0 | 0 | 0 | 0 | 0 | 0.128852 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.285714 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2 |
c17ba91b6eb327e7efe20742be1330903741437d | 696 | py | Python | locan/gui/__init__.py | super-resolution/Locan | 94ed7759f7d7ceddee7c7feaabff80010cfedf30 | [
"BSD-3-Clause"
] | 8 | 2021-11-25T20:05:49.000Z | 2022-03-27T17:45:00.000Z | locan/gui/__init__.py | super-resolution/Locan | 94ed7759f7d7ceddee7c7feaabff80010cfedf30 | [
"BSD-3-Clause"
] | 4 | 2021-12-15T22:39:20.000Z | 2022-03-11T17:35:34.000Z | locan/gui/__init__.py | super-resolution/Locan | 94ed7759f7d7ceddee7c7feaabff80010cfedf30 | [
"BSD-3-Clause"
] | 1 | 2022-03-22T19:53:13.000Z | 2022-03-22T19:53:13.000Z | """
User interfaces.
This module provides functions and classes for using graphical user interfaces (GUI).
Functions provide a GUI based on QT if the QT backend and appropriate python bindings
are available. Supported bindings are found in the enum class `locan.QtBindings`.
The configuration variable `locan.QT_BINDING` declares which python binding to use
if several are installed.
If an environment variable `QT_API` is defined it takes precedence over
`locan.QT_BINDING`.
If neither `locan.QT_BINDING` nor `QT_API` is defined, qtpy will choose the binding.
Submodules:
-----------
.. autosummary::
:toctree: ./
io
"""
from .io import *
__all__ = []
__all__.extend(io.__all__)
| 23.2 | 85 | 0.752874 | 99 | 696 | 5.121212 | 0.636364 | 0.04142 | 0.08284 | 0.055227 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.159483 | 696 | 29 | 86 | 24 | 0.866667 | 0.899425 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.333333 | 0 | 0.333333 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 2 |
c181c1f2aeaf3656347d6359b34e82466720a0f0 | 1,909 | py | Python | backend/api/tests/test_load_ops_data.py | amichard/zeva | 19ba22b07946674cc31a48c632aceca594a53e1a | [
"Apache-2.0"
] | null | null | null | backend/api/tests/test_load_ops_data.py | amichard/zeva | 19ba22b07946674cc31a48c632aceca594a53e1a | [
"Apache-2.0"
] | null | null | null | backend/api/tests/test_load_ops_data.py | amichard/zeva | 19ba22b07946674cc31a48c632aceca594a53e1a | [
"Apache-2.0"
] | null | null | null | # -*- coding: utf-8 -*-
# pylint: disable=no-member,invalid-name,duplicate-code
import importlib
import logging
from collections import namedtuple
from django.test import TestCase
class TestLoadOpsData(TestCase):
"""
Execute specified operational scripts to validate that they work
"""
ScriptDefinition = namedtuple(
'ScriptDefinition', ('file', 'args', 'skip'), defaults=('', False,)
)
scripts = [
ScriptDefinition(
'api.fixtures.operational.0000_add_government_organization'
),
ScriptDefinition(
'api.fixtures.operational.0001_add_vehicle_makes'
),
ScriptDefinition(
'api.fixtures.operational.0002_add_vehicle_classes'
),
ScriptDefinition(
'api.fixtures.operational.0003_add_vehicle_fuel_types'
),
ScriptDefinition(
'api.fixtures.operational.0004_add_model_years'
),
ScriptDefinition(
'api.fixtures.operational.0005_add_organizations'
),
ScriptDefinition(
'api.fixtures.test.0001_add_plugin_hybrid_vehicles'
),
ScriptDefinition(
'api.fixtures.test.0002_add_battery_electric_vehicles'
),
]
logger = logging.getLogger('zeva.test')
def testOperationalScripts(self):
for script in self.scripts:
if not script.skip:
with self.subTest('testing operational script {file}'.format(
file=script.file
)):
logging.info('loading script: {file}'.format(
file=script.file
))
loaded = importlib.import_module(script.file)
instance = loaded.script_class(script.file, script.args)
instance.check_run_preconditions()
instance.run()
| 31.816667 | 77 | 0.594552 | 168 | 1,909 | 6.577381 | 0.5 | 0.137557 | 0.195475 | 0.206335 | 0.054299 | 0.054299 | 0 | 0 | 0 | 0 | 0 | 0.025172 | 0.313253 | 1,909 | 59 | 78 | 32.355932 | 0.817696 | 0.073861 | 0 | 0.375 | 0 | 0 | 0.27984 | 0.227299 | 0 | 0 | 0 | 0 | 0 | 1 | 0.020833 | false | 0 | 0.104167 | 0 | 0.208333 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
c185e048dc4886bb52a9876c6481c0ebcf601a77 | 1,677 | py | Python | Chapter04/cnn/basics.py | PacktPublishing/Neural-Network-Programming-with-TensorFlow | 6ab03d8bfc8b23217968e7f71b656e3afc8bd7a0 | [
"MIT"
] | 26 | 2017-11-17T18:56:16.000Z | 2022-03-03T13:25:44.000Z | Chapter04/cnn/basics.py | PacktPublishing/Neural-Network-Programming-with-TensorFlow | 6ab03d8bfc8b23217968e7f71b656e3afc8bd7a0 | [
"MIT"
] | 2 | 2021-08-25T14:50:10.000Z | 2022-02-09T23:30:51.000Z | Chapter04/cnn/basics.py | PacktPublishing/Neural-Network-Programming-with-TensorFlow | 6ab03d8bfc8b23217968e7f71b656e3afc8bd7a0 | [
"MIT"
] | 22 | 2017-11-16T05:16:38.000Z | 2022-01-03T20:10:04.000Z | import tensorflow as tf
import numpy as np
def main():
# setup-only-ignore
sess = tf.InteractiveSession()
image_batch = tf.constant([
[ # First Image
[[255, 0, 0], [255, 0, 0], [0, 255, 0]],
[[255, 0, 0], [255, 0, 0], [0, 255, 0]]
],
[ # First Image
[[0, 0, 0], [0, 255, 0], [0, 255, 0]],
[[0, 0, 0], [0, 255, 0], [0, 255, 0]]
],
[ # Second Image
[[0, 0, 255], [0, 0, 255], [0, 0, 255]],
[[0, 0, 255], [0, 0, 255], [0, 0, 255]]
]
])
print(image_batch.get_shape())
print(sess.run(image_batch)[0][0][0])
i = tf.constant([
[
[1.0, 1.0, 1.0, 0.0, 0.0],
[0.0, 0.0, 1.0, 1.0, 1.0],
[0.0, 0.0, 1.0, 1.0, 0.0],
[0.0, 0.0, 1.0, 0.0, 0.0]
]
])
k = tf.constant([
[
[[1.0, 0.0, 1.0]],
[[0.0, 1.0, 0.0]],
[[1.0, 0.0, 1.0]]
]
])
kernel = tf.reshape(k, [3, 3, 1, 1], name='kernel')
image = tf.reshape(i, [1, 4, 5, 1], name='image')
conv2d = tf.nn.conv2d(image, kernel, strides=[1, 1, 1, 1], padding='VALID')
res = tf.squeeze(tf.nn.conv2d(image, kernel, [1, 1, 1, 1], "VALID"))
# VALID means no padding
with tf.Session() as sess:
print sess.run(res)
#tensor_out = sess.run(conv2d)
#print(tensor_out)
lower_right_image_pixel = sess.run(input_batch)[0][1][1]
lower_right_kernel_pixel = sess.run(conv2d)[0][1][1]
if __name__ == '__main__':
main() | 27.95 | 79 | 0.415623 | 249 | 1,677 | 2.714859 | 0.204819 | 0.156805 | 0.133136 | 0.100592 | 0.275148 | 0.213018 | 0.213018 | 0.207101 | 0.207101 | 0.118343 | 0 | 0.167792 | 0.381634 | 1,677 | 60 | 80 | 27.95 | 0.484089 | 0.073345 | 0 | 0.111111 | 0 | 0 | 0.018746 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0.044444 | null | null | 0.066667 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
c19392f70699347a257fa3153ab269b3faa89422 | 79 | py | Python | backend/fms_core/template_importer/row_handlers/sample_qc/__init__.py | c3g/freezeman | bc4b6c8a2876e888ce41b7d14127cc22bc2b2143 | [
"W3C"
] | 2 | 2021-07-31T13:20:08.000Z | 2021-09-28T13:18:55.000Z | backend/fms_core/template_importer/row_handlers/sample_qc/__init__.py | c3g/freezeman | bc4b6c8a2876e888ce41b7d14127cc22bc2b2143 | [
"W3C"
] | 71 | 2021-03-12T22:08:19.000Z | 2022-03-25T15:24:40.000Z | backend/fms_core/template_importer/row_handlers/sample_qc/__init__.py | c3g/freezeman | bc4b6c8a2876e888ce41b7d14127cc22bc2b2143 | [
"W3C"
] | null | null | null | from .sample import SampleQCRowHandler
__all__ = [
"SampleQCRowHandler",
] | 15.8 | 38 | 0.746835 | 6 | 79 | 9.166667 | 0.833333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.164557 | 79 | 5 | 39 | 15.8 | 0.833333 | 0 | 0 | 0 | 0 | 0 | 0.225 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.25 | 0 | 0.25 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
c19458c176cd079b9feeb51b3b17ea368d862156 | 185 | py | Python | MainLibPython/JsonHelper.py | emacslisp/pythonlib | 5f299b24c3c4ea56fed48ed71d4a4c826e1cb36b | [
"Apache-2.0"
] | null | null | null | MainLibPython/JsonHelper.py | emacslisp/pythonlib | 5f299b24c3c4ea56fed48ed71d4a4c826e1cb36b | [
"Apache-2.0"
] | null | null | null | MainLibPython/JsonHelper.py | emacslisp/pythonlib | 5f299b24c3c4ea56fed48ed71d4a4c826e1cb36b | [
"Apache-2.0"
] | null | null | null | import json
class JsonHelper:
def indentJson(self, jsonStr):
jsonObject = json.loads(jsonStr)
return json.dumps(jsonObject, sort_keys=True, indent=4, separators=(',', ': '))
| 26.428571 | 83 | 0.702703 | 22 | 185 | 5.863636 | 0.818182 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.006369 | 0.151351 | 185 | 6 | 84 | 30.833333 | 0.815287 | 0 | 0 | 0 | 0 | 0 | 0.016216 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.2 | false | 0 | 0.2 | 0 | 0.8 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
c1a086751b0b56a7f9ca05b577cff4bf8698dab4 | 371 | py | Python | 0304.Range Sum Query 2D - Immutable/test.py | zhlinh/leetcode | 6dfa0a4df9ec07b2c746a13c8257780880ea04af | [
"Apache-2.0"
] | null | null | null | 0304.Range Sum Query 2D - Immutable/test.py | zhlinh/leetcode | 6dfa0a4df9ec07b2c746a13c8257780880ea04af | [
"Apache-2.0"
] | null | null | null | 0304.Range Sum Query 2D - Immutable/test.py | zhlinh/leetcode | 6dfa0a4df9ec07b2c746a13c8257780880ea04af | [
"Apache-2.0"
] | null | null | null | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from solution import NumMatrix
matrix = [[3, 0, 1, 4, 2],
[5, 6, 3, 2, 1],
[1, 2, 0, 1, 5],
[4, 1, 0, 1, 7],
[1, 0, 3, 0, 5]]
numMatrix = NumMatrix(matrix)
print(numMatrix.sumRegion(2, 1, 4, 3))
print(numMatrix.sumRegion(1, 1, 2, 2))
print(numMatrix.sumRegion(1, 2, 2, 4))
| 23.1875 | 38 | 0.506739 | 61 | 371 | 3.081967 | 0.360656 | 0.031915 | 0.367021 | 0.255319 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.142857 | 0.283019 | 371 | 15 | 39 | 24.733333 | 0.56391 | 0.113208 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.1 | 0 | 0.1 | 0.3 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
c1d53d3cc1b5a5a9f331f03b0a0e8a4894db6cea | 2,666 | py | Python | functions/helpers/errors.py | haynieresearch/unusual_options_activity | f87619244bf72e603032bf5f66963b5a692bace2 | [
"Apache-2.0"
] | null | null | null | functions/helpers/errors.py | haynieresearch/unusual_options_activity | f87619244bf72e603032bf5f66963b5a692bace2 | [
"Apache-2.0"
] | null | null | null | functions/helpers/errors.py | haynieresearch/unusual_options_activity | f87619244bf72e603032bf5f66963b5a692bace2 | [
"Apache-2.0"
] | null | null | null | #**********************************************************
#* CATEGORY SOFTWARE
#* GROUP MARKET DATA
#* AUTHOR LANCE HAYNIE <LANCE@HAYNIEMAIL.COM>
#* DATE 2020-10-20
#* PURPOSE UNUSUAL OPTIONS ACTIVITY
#* FILE ERRORS.PY
#**********************************************************
#* MODIFICATIONS
#* 2020-10-20 - LHAYNIE - INITIAL VERSION
#**********************************************************
#UNUSUAL OPTIONS ACTIVITY
#Copyright 2020 Haynie IPHC, LLC
#Developed by Haynie Research & Development, LLC
#Licensed under the Apache License, Version 2.0 (the "License");
#you may not use this file except in compliance with the License.#
#You may obtain a copy of the License at
#http://www.apache.org/licenses/LICENSE-2.0
#Unless required by applicable law or agreed to in writing, software
#distributed under the License is distributed on an "AS IS" BASIS,
#WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
#See the License for the specific language governing permissions and
#limitations under the License.
import pyppeteer
class HttpErrors:
def handle_errors(response):
if response.status_code in [200, 201]:
return
elif 400 <= response.status_code < 500:
raise HttpClientError(response.status_code, response.url)
elif 500 <= response.status_code < 600:
raise HttpServerError(response.status_code, response.url)
def handle_render_errors(render_func, **kwargs):
try:
render_func(**kwargs)
except pyppeteer.errors.TimeoutError:
raise TimeoutError(msg='Timeout exceeded, try increasing the timeout value.')
class InvalidTimeoutValue(Exception):
"""Raise when timeout value is invalid"""
def __init__(self, val):
super(InvalidTimeoutValue, self).__init__(f'Timeout value cannot be empty and/or less than 1: {val}')
class TimeoutError(Exception):
"""Raise on timeout"""
def __init__(self, msg=''):
super(TimeoutError, self).__init__(msg)
class HttpClientError(Exception):
"""Raise on client error exception"""
def __init__(self, status_code, url):
super(HttpClientError, self).__init__(f'Client Error while fetching {url} with status code {status_code}')
class HttpServerError(Exception):
"""Raise on server error exception"""
def __init__(self, status_code, url):
super(HttpServerError, self).__init__(f'Server Error while fetching {url} with status code {status_code}')
class ParsingError(Exception):
"""Raises when parsing table heading and body"""
def __init__(self, msg=''):
super(ParsingError, self).__init__(f'Parsing error: {msg}')
class MissingParserType(Exception):
"""Raise when missing parser class"""
def __init__(self):
super(MissingParserType, self).__init__()
| 37.027778 | 108 | 0.708552 | 335 | 2,666 | 5.453731 | 0.438806 | 0.060208 | 0.036125 | 0.017515 | 0.154351 | 0.101806 | 0.101806 | 0.101806 | 0.101806 | 0.054735 | 0 | 0.018479 | 0.127157 | 2,666 | 71 | 109 | 37.549296 | 0.766652 | 0.443736 | 0 | 0.125 | 0 | 0 | 0.177747 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0 | 0.03125 | 0 | 0.53125 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2 |
c1d6668056f110c8a2e633807bedb961e5aebfe8 | 585 | py | Python | mlcomp/parallelm/common/buff_to_lines.py | lisapm/mlpiper | 74ad5ae343d364682cc2f8aaa007f2e8a1d84929 | [
"Apache-2.0"
] | 7 | 2019-04-08T02:31:55.000Z | 2021-11-15T14:40:49.000Z | mlcomp/parallelm/common/buff_to_lines.py | lisapm/mlpiper | 74ad5ae343d364682cc2f8aaa007f2e8a1d84929 | [
"Apache-2.0"
] | 31 | 2019-02-22T22:23:26.000Z | 2021-08-02T17:17:06.000Z | mlcomp/parallelm/common/buff_to_lines.py | lisapm/mlpiper | 74ad5ae343d364682cc2f8aaa007f2e8a1d84929 | [
"Apache-2.0"
] | 8 | 2019-03-15T23:46:08.000Z | 2020-02-06T09:16:02.000Z |
class BufferToLines(object):
def __init__(self):
self._acc_buff = ""
self._last_line = ""
self._in_middle_of_line = False
def add(self, buff):
self._acc_buff += buff.decode()
self._in_middle_of_line = False if self._acc_buff[-1] == '\n' else True
def lines(self):
lines = self._acc_buff.split('\n')
up_to_index = len(lines) - 2 if self._in_middle_of_line else len(lines) - 1
self._acc_buff = lines[-1] if self._in_middle_of_line else ""
for iii in range(up_to_index):
yield lines[iii]
| 30.789474 | 83 | 0.613675 | 88 | 585 | 3.670455 | 0.363636 | 0.108359 | 0.170279 | 0.173375 | 0.291022 | 0.291022 | 0.148607 | 0 | 0 | 0 | 0 | 0.009346 | 0.268376 | 585 | 18 | 84 | 32.5 | 0.745327 | 0 | 0 | 0 | 0 | 0 | 0.006849 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.214286 | false | 0 | 0 | 0 | 0.285714 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
c1da183dc12587113207c6d92f2597542e28bfb0 | 125 | py | Python | saltant/version.py | saltant-org/saltant-py | bf3bdbc4ec9c772c7f621f8bd6a76c5932af68be | [
"MIT"
] | null | null | null | saltant/version.py | saltant-org/saltant-py | bf3bdbc4ec9c772c7f621f8bd6a76c5932af68be | [
"MIT"
] | null | null | null | saltant/version.py | saltant-org/saltant-py | bf3bdbc4ec9c772c7f621f8bd6a76c5932af68be | [
"MIT"
] | null | null | null | """Contains name, version, and description."""
NAME = "saltant-py"
VERSION = "0.4.0"
DESCRIPTION = "saltant SDK for Python"
| 20.833333 | 46 | 0.688 | 17 | 125 | 5.058824 | 0.705882 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.028037 | 0.144 | 125 | 5 | 47 | 25 | 0.775701 | 0.32 | 0 | 0 | 0 | 0 | 0.468354 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
c1e78db39b9293d47d1aca0443c1c403366ec0a9 | 336 | py | Python | packages/jet_bridge_base/jet_bridge_base/messages.py | bokal2/jet-bridge | dddc4f55c2d5a28c02ce9515dffc750e3887450f | [
"MIT"
] | 1,247 | 2019-01-10T22:22:08.000Z | 2022-03-29T20:54:32.000Z | packages/jet_bridge_base/jet_bridge_base/messages.py | bokal2/jet-bridge | dddc4f55c2d5a28c02ce9515dffc750e3887450f | [
"MIT"
] | 12 | 2019-03-15T20:06:14.000Z | 2022-01-07T10:28:20.000Z | packages/jet_bridge_base/jet_bridge_base/messages.py | bokal2/jet-bridge | dddc4f55c2d5a28c02ce9515dffc750e3887450f | [
"MIT"
] | 130 | 2019-02-26T17:36:53.000Z | 2022-03-17T22:46:27.000Z |
GET_ACTION_LIST = 'get_action_list'
EXECUTE_ACTION = 'execute_action'
GET_FIELD_OPTIONS = 'get_field_options'
GET_ELEMENT_STATUS = 'get_element_status'
message_handlers = {}
def add_handler(message_name, func):
message_handlers[message_name] = func
def get_handler(message_name):
return message_handlers.get(message_name)
| 21 | 45 | 0.800595 | 46 | 336 | 5.347826 | 0.347826 | 0.178862 | 0.105691 | 0.146341 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.116071 | 336 | 15 | 46 | 22.4 | 0.828283 | 0 | 0 | 0 | 0 | 0 | 0.191045 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.222222 | false | 0 | 0 | 0.111111 | 0.333333 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 2 |
c1ef7e819e29408f1248eb8cf88bb0732cdda7d3 | 465 | py | Python | download-package/PythonExercises/ex015.py | MCLeitao/Python-Exercises | b24758ac6f95584ef03c320cc442c12a6fad2bd9 | [
"MIT"
] | null | null | null | download-package/PythonExercises/ex015.py | MCLeitao/Python-Exercises | b24758ac6f95584ef03c320cc442c12a6fad2bd9 | [
"MIT"
] | null | null | null | download-package/PythonExercises/ex015.py | MCLeitao/Python-Exercises | b24758ac6f95584ef03c320cc442c12a6fad2bd9 | [
"MIT"
] | null | null | null | # Write a program that asks the number of kilometers a car has driven and the number of days it has been hired.
# Calculate the price to pay, knowing that the car costs US$ 60 per day and US$ 0.15 per km driven.
k = float(input('Enter how many kilometers the car has traveled: '))
d = float(input('Enter how many days the car has been rented: '))
t = (k * 0.15) + (d * 60)
print('The total rental of the car is {}US${:.2f}{}'.format('\033[1;31;40m', t, '\033[m'))
| 58.125 | 111 | 0.68172 | 90 | 465 | 3.522222 | 0.566667 | 0.07571 | 0.069401 | 0.113565 | 0.138801 | 0 | 0 | 0 | 0 | 0 | 0 | 0.058201 | 0.187097 | 465 | 7 | 112 | 66.428571 | 0.780423 | 0.445161 | 0 | 0 | 0 | 0 | 0.611765 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.25 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
de02164fccb68242ed4a7b93d2d9462b419df145 | 1,012 | py | Python | symbol.py | thetaprimeio/flyingking-checkers | 96da039aa2e408b12eec78a5004dd38d2f05ace8 | [
"MIT"
] | null | null | null | symbol.py | thetaprimeio/flyingking-checkers | 96da039aa2e408b12eec78a5004dd38d2f05ace8 | [
"MIT"
] | null | null | null | symbol.py | thetaprimeio/flyingking-checkers | 96da039aa2e408b12eec78a5004dd38d2f05ace8 | [
"MIT"
] | null | null | null | asci = """
╔════╗╔╗ ╔╗ ╔═══╗ ╔══╗╔═══╗ ╔═══╗╔╗ ╔╗╔═╗
║╔╗╔╗║║║ ╔╝╚╗ ║╔═╗║ ╚╣╠╝║╔═╗║ ║╔══╝║║ ║║║╔╝
╚╝║║╚╝║╚═╗╔══╗╚╗╔╝╔══╗ ║╚═╝║╔═╗╔╗╔╗╔╗╔══╗ ║║ ║║ ║║ ╔═╗ ║╚══╗║║ ╔╗ ╔╗╔╗╔═╗ ╔══╗ ║╚╝╝ ╔╗╔═╗ ╔══╗
║║ ║╔╗║║╔╗║ ║║ ╚ ╗║ ║╔══╝║╔╝╠╣║╚╝║║╔╗║ ║║ ║║ ║║ ╚═╝ ║╔══╝║║ ║║ ║║╠╣║╔╗╗║╔╗║ ║╔╗║ ╠╣║╔╗╗║╔╗║
╔╝╚╗ ║║║║║║═╣ ║╚╗║╚╝╚╗║║ ║║ ║║║║║║║║═╣╔╗╔╣╠╗║╚═╝║ ╔═╗ ╔╝╚╗ ║╚╗║╚═╝║║║║║║║║╚╝║ ║║║╚╗║║║║║║║╚╝║
╚══╝ ╚╝╚╝╚══╝ ╚═╝╚═══╝╚╝ ╚╝ ╚╝╚╩╩╝╚══╝╚╝╚══╝╚═══╝ ╚═╝ ╚══╝ ╚═╝╚═╗╔╝╚╝╚╝╚╝╚═╗║ ╚╝╚═╝╚╝╚╝╚╝╚═╗║
╔═╝║ ╔═╝║ ╔═╝║
╚══╝ ╚══╝ ╚══╝
▄▀▀ █▄█ ██▀ ▄▀▀ █▄▀ ██▀ █▀▄ ▄▀▀ ▄▀▄ █ ▀█▀ █▀▄ ▄▀▄ █ █▄ █ ██▀ █▀▄
▀▄▄ █ █ █▄▄ ▀▄▄ █ █ █▄▄ █▀▄ ▄██ █▀█ █ █ █▀▄ █▀█ █ █ ▀█ █▄▄ █▀▄
"""
| 72.285714 | 106 | 0.003953 | 103 | 1,012 | 5.058252 | 0.543689 | 0.03071 | 0.023033 | 0.03071 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.478261 | 1,012 | 13 | 107 | 77.846154 | 0.007576 | 0 | 0 | 0 | 0 | 0 | 0.986166 | 0.063241 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
de0348ca9bc6b522e746cbbe2f2a9029bea33210 | 2,556 | py | Python | haystack/backends/dummy_backend.py | mcroydon/django-haystack | bdb0151cb85dc3a1b2bafcf9f5f410c9653a4ac5 | [
"BSD-3-Clause"
] | 1 | 2016-05-09T12:26:20.000Z | 2016-05-09T12:26:20.000Z | haystack/backends/dummy_backend.py | mcroydon/django-haystack | bdb0151cb85dc3a1b2bafcf9f5f410c9653a4ac5 | [
"BSD-3-Clause"
] | null | null | null | haystack/backends/dummy_backend.py | mcroydon/django-haystack | bdb0151cb85dc3a1b2bafcf9f5f410c9653a4ac5 | [
"BSD-3-Clause"
] | null | null | null | """
A fake backend for dummying during tests.
"""
import datetime
from django.db import models
from haystack.backends import BaseSearchBackend, BaseSearchQuery
from haystack.constants import FILTER_SEPARATOR
from haystack.models import SearchResult
class DummySearchResult(SearchResult):
dm = type('DummyModel', (object,), {})
def _get_object(self):
return self.dm()
def _set_object(self, obj):
pass
def _get_model(self):
return self.dm
def _set_model(self, obj):
pass
def content_type(self):
return u"%s.%s" % (self.app_label, self.module_name)
class SearchBackend(BaseSearchBackend):
def update(self, indexer, iterable):
pass
def remove(self, obj):
pass
def clear(self, models):
pass
def search(self, query_string, sort_by=None, start_offset=0, end_offset=None, fields=[], highlight=False):
if query_string == 'content__exact hello AND content__exact world':
return {
'results': [DummySearchResult('haystack', 'dummymodel', 1, 1.5)],
'hits': 1,
}
return {
'results': [],
'hits': 0,
}
def prep_value(self, db_field, value):
return value
def more_like_this(self, model_instance):
return {
'results': [],
'hits': 0
}
class SearchQuery(BaseSearchQuery):
def __init__(self, backend=None):
super(SearchQuery, self).__init__(backend=backend)
self.backend = backend or SearchBackend()
def build_query(self):
filters = []
for the_filter in self.query_filters:
filter_list = []
if the_filter.is_and():
filter_list.append("AND")
elif the_filter.is_not():
filter_list.append("NOT")
elif the_filter.is_or():
filter_list.append("OR")
filter_list.append(FILTER_SEPARATOR.join((the_filter.field, the_filter.filter_type)))
filter_list.append(the_filter.value)
if not len(filters):
del(filter_list[0])
filters.append(" ".join(filter_list))
query = " ".join(filters)
if self.order_by:
query = "%s ORDER BY %s" % (query, ", ".join(self.order_by))
return query
def clean(self, query_fragment):
return query_fragment
| 26.350515 | 110 | 0.565336 | 277 | 2,556 | 5 | 0.34657 | 0.057762 | 0.057762 | 0.030325 | 0.031769 | 0.031769 | 0 | 0 | 0 | 0 | 0 | 0.004678 | 0.330986 | 2,556 | 96 | 111 | 26.625 | 0.805263 | 0.016041 | 0 | 0.151515 | 0 | 0 | 0.054647 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.212121 | false | 0.075758 | 0.075758 | 0.090909 | 0.484848 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 |
a9c4f7a863a238f325490e8bb2c4f36b6463e0f0 | 67 | py | Python | 1002.py | heltonricardo/URI | 160cca22d94aa667177c9ebf2a1c9864c5e55b41 | [
"MIT"
] | 6 | 2021-04-13T00:33:43.000Z | 2022-02-10T10:23:59.000Z | 1002.py | heltonricardo/URI | 160cca22d94aa667177c9ebf2a1c9864c5e55b41 | [
"MIT"
] | null | null | null | 1002.py | heltonricardo/URI | 160cca22d94aa667177c9ebf2a1c9864c5e55b41 | [
"MIT"
] | 3 | 2021-03-23T18:42:24.000Z | 2022-02-10T10:24:07.000Z | r = float(input())
a = r * r * 3.14159
print('A={:.4f}'.format(a))
| 16.75 | 27 | 0.522388 | 13 | 67 | 2.692308 | 0.692308 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.125 | 0.164179 | 67 | 3 | 28 | 22.333333 | 0.5 | 0 | 0 | 0 | 0 | 0 | 0.119403 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.333333 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
a9cd438d188e21a7dfc68691d19c29be199f68db | 1,836 | py | Python | PyPoE/ui/__init__.py | Gloorf/PyPoE | 23e60e0914a1a669764a552f762d2b2064203e75 | [
"MIT"
] | 247 | 2015-07-06T19:39:11.000Z | 2022-03-30T13:11:03.000Z | PyPoE/ui/__init__.py | Gloorf/PyPoE | 23e60e0914a1a669764a552f762d2b2064203e75 | [
"MIT"
] | 121 | 2015-09-01T23:50:22.000Z | 2021-08-23T21:06:47.000Z | PyPoE/ui/__init__.py | Gloorf/PyPoE | 23e60e0914a1a669764a552f762d2b2064203e75 | [
"MIT"
] | 109 | 2015-09-09T06:37:56.000Z | 2022-03-20T16:06:33.000Z | """
UI Code
Overview
===============================================================================
+----------+------------------------------------------------------------------+
| Path | PyPoE/ui/__init__.py |
+----------+------------------------------------------------------------------+
| Version | 1.0.0a0 |
+----------+------------------------------------------------------------------+
| Revision | $Id: a9cd438d188e21a7dfc68691d19c29be199f68db $ |
+----------+------------------------------------------------------------------+
| Author | Omega_K2 |
+----------+------------------------------------------------------------------+
Description
===============================================================================
Agreement
===============================================================================
See PyPoE/LICENSE
"""
# =============================================================================
# Imports
# =============================================================================
# Python
# 3rd-party
# self
from PyPoE.ui.ggpk_viewer import GGPKViewerMainWindow
from PyPoE.ui.launchpad import launchpad_main
# =============================================================================
# Globals
# =============================================================================
__all__ = []
_apps = [GGPKViewerMainWindow]
# =============================================================================
# Entry point
# =============================================================================
def main(*args, **kwargs):
launchpad_main(_apps, *args, **kwargs)
if __name__ == '__main__':
main() | 32.210526 | 79 | 0.204793 | 61 | 1,836 | 5.803279 | 0.704918 | 0.059322 | 0.062147 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.019468 | 0.160675 | 1,836 | 57 | 80 | 32.210526 | 0.210253 | 0.839869 | 0 | 0 | 0 | 0 | 0.028986 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.125 | false | 0 | 0.25 | 0 | 0.375 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
a9df176c0ed713e3cddce7c43a695bb1378443c0 | 823 | py | Python | learn/notebook.py | murakrishn/aima-python | 5686c87bcfd3eb23be4a55d3e69762c98d88be23 | [
"MIT"
] | null | null | null | learn/notebook.py | murakrishn/aima-python | 5686c87bcfd3eb23be4a55d3e69762c98d88be23 | [
"MIT"
] | null | null | null | learn/notebook.py | murakrishn/aima-python | 5686c87bcfd3eb23be4a55d3e69762c98d88be23 | [
"MIT"
] | null | null | null | from ast import Import
from inspect import getsource
import ipywidgets as widgets
import matplotlib.pyplot as plt
import networkx as nx
import numpy as np
from IPython.display import HTML
from IPython.display import display
from PIL import Image
from matplotlib import lines
# ----------------------------------------------------------------------
# Magic words
def psource(*functions):
"""Print the pseudocode for the given algorithms"""
source_code = '\n\n'.join(getsource(fn) for fn in functions)
# print(source_code)
try:
from pygments.formatters import HtmlFormatter
from pygments.lexers import PythonLexer
from pygments import highlight
display(HTML(highlight(source_code, PythonLexer(), HtmlFormatter(full=True))))
except ImportError:
print(source_code) | 31.653846 | 86 | 0.682868 | 98 | 823 | 5.693878 | 0.5 | 0.071685 | 0.064516 | 0.086022 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.17497 | 823 | 26 | 87 | 31.653846 | 0.821797 | 0.17983 | 0 | 0 | 0 | 0 | 0.005988 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.052632 | false | 0 | 0.736842 | 0 | 0.789474 | 0.052632 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 2 |
a9ea04f5f071c7e8e4f777207f4e9928ee49d868 | 277 | py | Python | experiments/messaging/http/http_client.py | chartbeat-labs/wade | 91923ed10bee4b2f084b156b31d4e4700bf2326c | [
"Apache-2.0"
] | 16 | 2016-01-27T22:07:51.000Z | 2020-04-26T01:23:05.000Z | experiments/messaging/http/http_client.py | chartbeat-labs/wade | 91923ed10bee4b2f084b156b31d4e4700bf2326c | [
"Apache-2.0"
] | 4 | 2016-02-03T22:00:39.000Z | 2016-02-29T18:33:02.000Z | experiments/messaging/http/http_client.py | chartbeat-labs/wade | 91923ed10bee4b2f084b156b31d4e4700bf2326c | [
"Apache-2.0"
] | 4 | 2016-01-27T22:30:09.000Z | 2019-02-17T02:02:18.000Z |
import time
import requests
if __name__ == '__main__':
num = 10000
s = requests.Session()
st_time = time.time()
for i in xrange(num):
s.get('http://127.0.0.1:8088/')
diff_time = time.time() - st_time
print num / diff_time, "requests / sec"
| 17.3125 | 43 | 0.599278 | 41 | 277 | 3.756098 | 0.585366 | 0.207792 | 0.155844 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.072816 | 0.256318 | 277 | 15 | 44 | 18.466667 | 0.674757 | 0 | 0 | 0 | 0 | 0 | 0.15942 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0.2 | null | null | 0.1 | 0 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
a9ed49fcbe30270e1bc48cb1dbe0513fa398d66b | 818 | py | Python | mod/database.py | 404neko/bridge | 56ed1095aff88b997107f42fd7a4b39d0b92aea7 | [
"MIT"
] | null | null | null | mod/database.py | 404neko/bridge | 56ed1095aff88b997107f42fd7a4b39d0b92aea7 | [
"MIT"
] | null | null | null | mod/database.py | 404neko/bridge | 56ed1095aff88b997107f42fd7a4b39d0b92aea7 | [
"MIT"
] | null | null | null | from peewee import *
database = MySQLDatabase('shortlink', **{'host': '106.185.40.164', 'password': 'AlexprprHaoqiao', 'port': 3306, 'user': 'root'})
class BaseModel(Model):
class Meta:
database = database
class Pool(BaseModel):
#data = TextField(null=False)
time = DateTimeField(null=True)
url = TextField(null=False)
uid = TextField(null=False)
title = TextField(null=False)
content = TextField(null=False)
#did = CharField(null=False)
class Meta:
db_table = 'pool'
class Record(BaseModel):
time = DateTimeField(null=False)
ip = TextField(null=False)
ua = TextField(null=False)
referer = TextField(null=False)
class Meta:
db_table = 'record'
if __name__ == '__main__':
Pool.create_table(True)
Record.create_table(True) | 23.371429 | 128 | 0.654034 | 95 | 818 | 5.505263 | 0.473684 | 0.172084 | 0.275335 | 0.068834 | 0.095602 | 0.095602 | 0 | 0 | 0 | 0 | 0 | 0.02322 | 0.210269 | 818 | 35 | 129 | 23.371429 | 0.786378 | 0.067237 | 0 | 0.130435 | 0 | 0 | 0.104987 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0.043478 | 0.043478 | 0 | 0.695652 | 0 | 0 | 0 | 0 | null | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2 |
a9f31d04658b06313ec151cdf48ee8a69f7d6a60 | 1,145 | py | Python | tools/grit/grit/format/interface.py | JoKaWare/WTL-DUI | 89fd6f4ed7e6a4ce85f9af29c40de0d9a85ca8b2 | [
"BSD-3-Clause"
] | 19 | 2015-03-30T09:49:58.000Z | 2020-01-17T20:05:12.000Z | tools/grit/grit/format/interface.py | jjzhang166/WTL-DUI | 89fd6f4ed7e6a4ce85f9af29c40de0d9a85ca8b2 | [
"BSD-3-Clause"
] | 1 | 2015-12-31T06:08:27.000Z | 2015-12-31T06:08:27.000Z | tools/grit/grit/format/interface.py | jjzhang166/WTL-DUI | 89fd6f4ed7e6a4ce85f9af29c40de0d9a85ca8b2 | [
"BSD-3-Clause"
] | 11 | 2015-06-01T06:18:03.000Z | 2020-05-10T07:18:53.000Z | #!/usr/bin/env python
# Copyright (c) 2012 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
'''Base classes for item formatters and file formatters.
'''
import re
class ItemFormatter(object):
"""Base class for a formatter that knows how to format a single item."""
def Format(self, item, lang='', output_dir='.'):
"""Format the start of this item.
Returns a Unicode string representing 'item' in the format known by this
item formatter, for the language 'lang'.
Args:
item: anything.
lang: 'en'
output_dir: '.'
Returns:
A unicode string.
"""
return ''
def FormatEnd(self, item, lang='', output_dir='.'):
"""Format the end of this item.
Returns a Unicode string representing the closure of 'item' in the
format known by this item formatter, for the language 'lang'.
Called (optionally) after the children of item have been formatted.
Args:
item: anything
lang: 'en'
output_dir: '.'
Returns:
A unicode string.
"""
return ''
| 23.854167 | 76 | 0.652402 | 158 | 1,145 | 4.702532 | 0.468354 | 0.048452 | 0.080754 | 0.113055 | 0.506057 | 0.506057 | 0.506057 | 0.425303 | 0.309556 | 0.309556 | 0 | 0.004651 | 0.248908 | 1,145 | 47 | 77 | 24.361702 | 0.859302 | 0.737991 | 0 | 0.333333 | 0 | 0 | 0.010152 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.333333 | false | 0 | 0.166667 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2 |
e7051544d72cc51a84e114c6f95ef49033855fe8 | 330 | py | Python | models/model.py | MarLisiecki/asm_tree_drawer | 31528e76cf9ff239ddd4385fd71e4bf4ee0c3e63 | [
"MIT"
] | null | null | null | models/model.py | MarLisiecki/asm_tree_drawer | 31528e76cf9ff239ddd4385fd71e4bf4ee0c3e63 | [
"MIT"
] | null | null | null | models/model.py | MarLisiecki/asm_tree_drawer | 31528e76cf9ff239ddd4385fd71e4bf4ee0c3e63 | [
"MIT"
] | null | null | null | from dataclasses import dataclass
# Mnemonic model which contains root label, target label, name of jump as mnemonic (e.g. jnp) and jump_type, which is
# the description of jump (e.g. Jump if not equal)
@dataclass(frozen=True)
class Mnemonic:
name: str
jump_type: str
target_label: str
root: str
| 27.5 | 117 | 0.693939 | 50 | 330 | 4.52 | 0.6 | 0.097345 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.239394 | 330 | 11 | 118 | 30 | 0.900398 | 0.49697 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.142857 | 0 | 0.857143 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 2 |
e72da99e34d29a403f8928cc9a39320753ff4f43 | 1,090 | py | Python | setup.py | gbtami/gbulb | a2d73a1aaf0fb0408deb546af0028eec842eaa1f | [
"Apache-2.0"
] | null | null | null | setup.py | gbtami/gbulb | a2d73a1aaf0fb0408deb546af0028eec842eaa1f | [
"Apache-2.0"
] | 1 | 2020-06-11T14:59:20.000Z | 2020-06-11T15:36:48.000Z | setup.py | gbtami/gbulb | a2d73a1aaf0fb0408deb546af0028eec842eaa1f | [
"Apache-2.0"
] | 1 | 2020-02-27T23:10:53.000Z | 2020-02-27T23:10:53.000Z | #!/usr/bin/env python
try:
from setuptools import setup
except ImportError:
from distutils.core import setup
setup(
name='gbulb',
version='0.6.1',
description='GLib event loop for tulip (PEP 3156)',
author='Nathan Hoad',
author_email='nathan@getoffmalawn.com',
license='Apache 2.0',
url='http://github.com/nathan-hoad/gbulb',
packages=['gbulb'],
long_description="""Gbulb is a python library that implements a PEP 3156 interface for the GLib main event loop. It is designed to be used together with the tulip reference implementation.""",
classifiers=[
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: Apache Software License",
"Operating System :: POSIX",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.5",
"Programming Language :: Python :: 3.6",
"Programming Language :: Python :: 3.7",
"Topic :: Software Development :: Libraries :: Python Modules",
],
python_requires='>3.5'
)
| 34.0625 | 196 | 0.643119 | 129 | 1,090 | 5.410853 | 0.627907 | 0.108883 | 0.143266 | 0.148997 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.027348 | 0.22844 | 1,090 | 31 | 197 | 35.16129 | 0.802616 | 0.018349 | 0 | 0 | 0 | 0.037037 | 0.602432 | 0.021515 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.111111 | 0 | 0.111111 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
e730bc3fbfd38821bf3551e776a6b0fb822ff3a1 | 1,633 | py | Python | algorithms/ML/supervised/knn.py | agdenadel/python-algorithms | 28c298e2bc311c609f39a9f1c75a5abc9cc66b8a | [
"MIT"
] | null | null | null | algorithms/ML/supervised/knn.py | agdenadel/python-algorithms | 28c298e2bc311c609f39a9f1c75a5abc9cc66b8a | [
"MIT"
] | null | null | null | algorithms/ML/supervised/knn.py | agdenadel/python-algorithms | 28c298e2bc311c609f39a9f1c75a5abc9cc66b8a | [
"MIT"
] | null | null | null | from collections import Counter
class KNN:
""" Implements K Nearest Neighbors classifier. """
def __init__(self, k, distance_function):
"""
Args:
k (int): The number of neighbors used for voting
distance_function (function(point, point)): A function used to compute the distance between two points
"""
self.k = k
self.distance_function = distance_function
@staticmethod
def vote(nearest_neighbors):
""" Returns the most common label among the k nearest neighbors
Args:
nearest_neighbors (iterable): The k nearest neighbors
"""
labels = Counter(map(lambda x: x.label, nearest_neighbors))
winning_label = max(labels, key=labels.get)
return winning_label
def predict(self, test_value, training_set):
"""
Predicts label for a point using the k nearest neighbors algorithm.
Args:
test_value:
training_set:
"""
nearest_neighbors = sorted(training_set,
key=lambda x: self.distance_function(test_value.coordinate, x.coordinate))[0:self.k]
return self.vote(nearest_neighbors)
def predict_multiple(self, test_values, training_set):
"""
Predicts labels for multiple points using the k nearest neighbors algorithm.
Args:
test_values (iterable):
training_set (iterable):
"""
return map(lambda test_value: self.predict(test_value, training_set), test_values) | 32.66 | 120 | 0.602572 | 178 | 1,633 | 5.353933 | 0.342697 | 0.167891 | 0.089192 | 0.083945 | 0.088143 | 0.088143 | 0.088143 | 0.088143 | 0 | 0 | 0 | 0.000904 | 0.322719 | 1,633 | 50 | 121 | 32.66 | 0.860759 | 0.353337 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0 | 0.0625 | 0 | 0.5625 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2 |
e73bf37fe11519cc201138caf5dd314b0e59280f | 246 | py | Python | Mundo 1/ex029.py | othiagomanhaes/Python | 8cfe6d50e31f6c9ff886e3961051cc4cbfb8569e | [
"MIT"
] | null | null | null | Mundo 1/ex029.py | othiagomanhaes/Python | 8cfe6d50e31f6c9ff886e3961051cc4cbfb8569e | [
"MIT"
] | null | null | null | Mundo 1/ex029.py | othiagomanhaes/Python | 8cfe6d50e31f6c9ff886e3961051cc4cbfb8569e | [
"MIT"
] | null | null | null | vel = int(input('Qual foi a velocidade do carro? '))
if vel > 80:
print('Seu carro está acima da velocidade permitida que é 80km/h!!')
multa = (vel - 80) * 7
print('Você será multado em R${} reais'.format(multa))
print('Boa viagem!')
| 35.142857 | 72 | 0.646341 | 40 | 246 | 3.975 | 0.8 | 0.062893 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.035714 | 0.203252 | 246 | 6 | 73 | 41 | 0.77551 | 0 | 0 | 0 | 0 | 0 | 0.54065 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.5 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 2 |
e74171b70498da7835d5b1cf3fdde8365a86d3ad | 1,183 | py | Python | cloudrail/knowledge/rules/aws/non_context_aware/iam_no_human_users_rule.py | my-devops-info/cloudrail-knowledge | b7c1bbd6fe1faeb79c105a01c0debbe24d031a0e | [
"MIT"
] | null | null | null | cloudrail/knowledge/rules/aws/non_context_aware/iam_no_human_users_rule.py | my-devops-info/cloudrail-knowledge | b7c1bbd6fe1faeb79c105a01c0debbe24d031a0e | [
"MIT"
] | null | null | null | cloudrail/knowledge/rules/aws/non_context_aware/iam_no_human_users_rule.py | my-devops-info/cloudrail-knowledge | b7c1bbd6fe1faeb79c105a01c0debbe24d031a0e | [
"MIT"
] | null | null | null | from typing import Dict, List
from cloudrail.knowledge.context.aws.aws_environment_context import AwsEnvironmentContext
from cloudrail.knowledge.rules.aws.aws_base_rule import AwsBaseRule
from cloudrail.knowledge.rules.base_rule import Issue
from cloudrail.knowledge.rules.rule_parameters.base_paramerter import ParameterType
class IamNoHumanUsersRule(AwsBaseRule):
def execute(self, env_context: AwsEnvironmentContext, parameters: Dict[ParameterType, any]) -> List[Issue]:
issues_list: List[Issue] = []
for user in env_context.users:
if any(user.name == login_profile.name and user.account == login_profile.account for login_profile in env_context.users_login_profile):
issues_list.append(Issue(f'The {user.get_type()} `{user.get_friendly_name()}` has console access, '
f'and so is considered human', user, user))
return issues_list
def get_id(self) -> str:
return "non_car_iam_no_human_users"
def should_run_rule(self, environment_context: AwsEnvironmentContext) -> bool:
return bool(environment_context.users and environment_context.users_login_profile)
| 51.434783 | 147 | 0.742181 | 149 | 1,183 | 5.66443 | 0.402685 | 0.07109 | 0.104265 | 0.095972 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.177515 | 1,183 | 22 | 148 | 53.772727 | 0.86742 | 0 | 0 | 0 | 0 | 0 | 0.103973 | 0.045647 | 0 | 0 | 0 | 0 | 0 | 1 | 0.176471 | false | 0 | 0.294118 | 0.117647 | 0.705882 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 2 |
e7511f8270f75b24221d1d0cbcb03ce52d8033c7 | 4,194 | py | Python | lianjiahouse/lianjiahouse/spiders/lianjia.py | Liu-Yichuan/- | eb3d1655cce3d2064f31f9420880bef6280a6dbd | [
"Apache-2.0"
] | 4 | 2020-09-16T07:55:08.000Z | 2021-12-06T16:05:44.000Z | lianjiahouse/lianjiahouse/spiders/lianjia.py | Liu-Yichuan/- | eb3d1655cce3d2064f31f9420880bef6280a6dbd | [
"Apache-2.0"
] | null | null | null | lianjiahouse/lianjiahouse/spiders/lianjia.py | Liu-Yichuan/- | eb3d1655cce3d2064f31f9420880bef6280a6dbd | [
"Apache-2.0"
] | null | null | null | # -*- coding: utf-8 -*-
#import scrapy
# class LianjiaSpider(scrapy.Spider):
# name = 'lianjia'
# allowed_domains = [''https://sy.lianjia.com/ershoufang/'']
# start_urls = ['http://'https://sy.lianjia.com/ershoufang/'/']
#
# def parse(self, response):
# pass
from scrapy import Request
from scrapy.spiders import Spider
from lianjiahouse.items import LianjiahouseItem
class house_chart(Spider):
name = 'lianjia'
headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/53.0.2785.143 Safari/537.36',
}
def start_requests(self):
start_url = 'https://sy.lianjia.com/ershoufang/'
yield Request(url=start_url,headers=self.headers)
def parse(self, response):
house_list = response.xpath('//div[@class="info clear"]/div[@class="title"]/a/@href')
for node in house_list:
href = node.extract()
yield Request(url=href,headers=self.headers,callback=self.parse1)
#实现翻页
for i in range(11):
if i != 0 and i != 1:
next_url = 'https://sy.lianjia.com/ershoufang/pg%d' % i
if next_url:
yield Request(url=next_url,headers=self.headers,callback=self.parse)
def parse1(self,response):
item = LianjiahouseItem()
item['totalprice'] = response.xpath('//div[@class="price "]/span[@class="total"]/text()').extract()[0]
item['price'] = response.xpath('//div[@class="unitPrice"]/span[@class="unitPriceValue"]/text()').extract()[0]
item['house_model'] = response.xpath('//div[@class="base"]/div[@class="content"]/ul/li[1]/text()').extract()[0]
item['floor'] = response.xpath('//div[@class="base"]/div[@class="content"]/ul/li[2]/text()').extract()[0]
item['area'] = response.xpath('//div[@class="base"]/div[@class="content"]/ul/li[3]/text()').extract()[0]
item['structure'] = response.xpath('//div[@class="base"]/div[@class="content"]/ul/li[4]/text()').extract()[0]
item['space_in'] = response.xpath('//div[@class="base"]/div[@class="content"]/ul/li[5]/text()').extract()[0]
item['build_type'] = response.xpath('//div[@class="base"]/div[@class="content"]/ul/li[6]/text()').extract()[0]
item['build_head'] = response.xpath('//div[@class="base"]/div[@class="content"]/ul/li[7]/text()').extract()[0]
item['build_struc'] = response.xpath('//div[@class="base"]/div[@class="content"]/ul/li[8]/text()').extract()[0]
item['decorate'] = response.xpath('//div[@class="base"]/div[@class="content"]/ul/li[9]/text()').extract()[0]
item['proportion'] = response.xpath('//div[@class="base"]/div[@class="content"]/ul/li[10]/text()').extract()[0]
item['heating_meth'] = response.xpath('//div[@class="base"]/div[@class="content"]/ul/li[11]/text()').extract()[0]
item['elevator'] = response.xpath('//div[@class="base"]/div[@class="content"]/ul/li[12]/text()').extract()[0]
item['year_pro'] = response.xpath('//div[@class="base"]/div[@class="content"]/ul/li[13]/text()').extract()[0]
item['time'] = response.xpath('//div[@class="transaction"]/div[@class="content"]/ul/li[1]/span[2]/text()').extract()[0]
item['trans'] = response.xpath('//div[@class="transaction"]/div[@class="content"]/ul/li[2]/span[2]/text()').extract()[0]
item['last_trans'] = response.xpath('//div[@class="transaction"]/div[@class="content"]/ul/li[3]/span[2]/text()').extract()[0]
item['usage'] = response.xpath('//div[@class="transaction"]/div[@class="content"]/ul/li[4]/span[2]/text()').extract()[0]
item['build_pro'] = response.xpath('//div[@class="transaction"]/div[@class="content"]/ul/li[5]/span[2]/text()').extract()[0]
item['belonging'] = response.xpath('//div[@class="transaction"]/div[@class="content"]/ul/li[6]/span[2]/text()').extract()[0]
item['mortgaga_info'] = response.xpath('//div[@class="transaction"]/div[@class="content"]/ul/li[7]/span[2]/text()').extract()[0]
item['room_parts'] = response.xpath('//div[@class="transaction"]/div[@class="content"]/ul/li[8]/span[2]/text()').extract()[0]
yield item | 64.523077 | 139 | 0.607535 | 564 | 4,194 | 4.478723 | 0.223404 | 0.145685 | 0.152019 | 0.199525 | 0.567696 | 0.480206 | 0.391924 | 0.391924 | 0.391924 | 0.391924 | 0 | 0.025208 | 0.139247 | 4,194 | 65 | 140 | 64.523077 | 0.674515 | 0.063901 | 0 | 0 | 0 | 0.468085 | 0.486466 | 0.375128 | 0 | 0 | 0 | 0 | 0 | 1 | 0.06383 | false | 0 | 0.06383 | 0 | 0.191489 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
e75b59d33523dde01a3913d32191191f014f87f2 | 593 | py | Python | ABC/abc001-abc050/abc032/a.py | KATO-Hiro/AtCoder | cbbdb18e95110b604728a54aed83a6ed6b993fde | [
"CC0-1.0"
] | 2 | 2020-06-12T09:54:23.000Z | 2021-05-04T01:34:07.000Z | ABC/abc001-abc050/abc032/a.py | KATO-Hiro/AtCoder | cbbdb18e95110b604728a54aed83a6ed6b993fde | [
"CC0-1.0"
] | 961 | 2020-06-23T07:26:22.000Z | 2022-03-31T21:34:52.000Z | ABC/abc001-abc050/abc032/a.py | KATO-Hiro/AtCoder | cbbdb18e95110b604728a54aed83a6ed6b993fde | [
"CC0-1.0"
] | null | null | null | '''input
97
89
20000
25899
10
5
8
10
97
89
8634
17266
97
89
8633
8633
100
100
101
200
1
1
1
1
1
1
20000
20000
100
100
20000
20000
12
8
25
48
2
3
8
12
2
2
2
2
'''
# -*- coding: utf-8 -*-
# AtCoder Beginner Contest
# Problem A
if __name__ == '__main__':
a = int(input())
b = int(input())
n = int(input())
# See:
# https://beta.atcoder.jp/contests/abc032/submissions/2264731
for i in range(n, 30000 + 1):
if i % a == 0 and i % b == 0:
print(i)
exit()
| 7.906667 | 66 | 0.48398 | 92 | 593 | 3.032609 | 0.543478 | 0.035842 | 0.043011 | 0.043011 | 0.021505 | 0 | 0 | 0 | 0 | 0 | 0 | 0.352273 | 0.406408 | 593 | 74 | 67 | 8.013514 | 0.440341 | 0.48398 | 0 | 0 | 0 | 0 | 0.036364 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.125 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
e76dd747e199cd130685c17c41e7e62cfab210ba | 849 | py | Python | catalog/migrations/0018_auto_20190809_1907.py | esalascolas/blog_diari | 43f6d22db745a38559fc2dcb8ea52c39a9d28753 | [
"MIT"
] | null | null | null | catalog/migrations/0018_auto_20190809_1907.py | esalascolas/blog_diari | 43f6d22db745a38559fc2dcb8ea52c39a9d28753 | [
"MIT"
] | 13 | 2020-02-11T22:06:44.000Z | 2022-02-10T08:23:36.000Z | catalog/migrations/0018_auto_20190809_1907.py | esalascolas/blog_diari | 43f6d22db745a38559fc2dcb8ea52c39a9d28753 | [
"MIT"
] | null | null | null | # Generated by Django 2.0.1 on 2019-08-09 17:07
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('catalog', '0017_remove_trip_route_trip_image'),
]
operations = [
migrations.AlterField(
model_name='plannedtrip',
name='hero_image',
field=models.ImageField(blank=True, help_text='Imatge hero', upload_to='plannedtrip'),
),
migrations.AlterField(
model_name='planstatusupdate',
name='day_image',
field=models.ImageField(blank=True, upload_to='plannedtripDay'),
),
migrations.AlterField(
model_name='redactor',
name='hero_image',
field=models.ImageField(blank=True, help_text='Imatge hero', upload_to='redactor'),
),
]
| 29.275862 | 98 | 0.608952 | 87 | 849 | 5.758621 | 0.517241 | 0.11976 | 0.149701 | 0.173653 | 0.345309 | 0.345309 | 0.275449 | 0.275449 | 0.275449 | 0.275449 | 0 | 0.030794 | 0.273263 | 849 | 28 | 99 | 30.321429 | 0.781199 | 0.053004 | 0 | 0.363636 | 1 | 0 | 0.198254 | 0.041147 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.045455 | 0 | 0.181818 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
e76f7f390c533fc963121728f5eae3cc5c96820f | 161 | py | Python | pylite/__init__.py | dariubs/pylite | 79258a07b8d84e7df802fc57721bb339b2f589c5 | [
"MIT"
] | 12 | 2019-12-04T19:00:44.000Z | 2021-08-21T10:16:09.000Z | pylite/__init__.py | dariubs/simplite.py | 79258a07b8d84e7df802fc57721bb339b2f589c5 | [
"MIT"
] | 1 | 2020-11-30T18:18:08.000Z | 2020-11-30T18:18:08.000Z | pylite/__init__.py | dariubs/pylite | 79258a07b8d84e7df802fc57721bb339b2f589c5 | [
"MIT"
] | 4 | 2019-06-29T16:21:31.000Z | 2020-05-03T08:15:04.000Z | # -*- coding: utf-8 -*-
"""
pylite
~~~~~~~~~
:copyright: (c) 2014 by Dariush Abbasi.
:license: MIT, see LICENSE for more details.
"""
__version__ = "0.1.0"
| 16.1 | 45 | 0.57764 | 21 | 161 | 4.238095 | 0.904762 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.061069 | 0.186335 | 161 | 9 | 46 | 17.888889 | 0.618321 | 0.770186 | 0 | 0 | 0 | 0 | 0.2 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
e78e555e6bbded5983da12da7c36b56b1a6626bb | 2,292 | py | Python | preapp/technologies/react.py | najaco/preapp | 6206d4cee68f9b6a63d4e1661c7c439012fc5ce0 | [
"MIT"
] | null | null | null | preapp/technologies/react.py | najaco/preapp | 6206d4cee68f9b6a63d4e1661c7c439012fc5ce0 | [
"MIT"
] | null | null | null | preapp/technologies/react.py | najaco/preapp | 6206d4cee68f9b6a63d4e1661c7c439012fc5ce0 | [
"MIT"
] | null | null | null | from preapp.hooks import action_hook
from preapp.node import Node
from preapp.utils.miscellaneous import bash
from preapp.utils.githubio import commit_and_push
from preapp.utils import __assets_directory__
import os
from preapp.utils.fileio import (
append_file_to_file,
copy_file,
delete_file,
file_to_text,
)
@action_hook("framework", "web_frontend", "react")
def setup():
project_name: str = Node.get_full_response()["metadata"]["name"]
if not Node.get_full_response()["github"]["use"]:
bash(f"npx create-react-app {project_name}")
else:
github_username: str = Node.get_full_response()["github_credentials"]["username"]
github_auth: str = ""
if "password" in Node.get_full_response()["github_credentials"]:
github_auth = Node.get_full_response()["github_credentials"]["password"]
if "oauth_token" in Node.get_full_response()["github_credentials"]:
github_auth = Node.get_full_response()["github_credentials"]["oauth_token"]
bash(f"cd {project_name} && npx create-react-app website")
# gitignore_file_path: str = f"{os.getcwd()}/{project_name}/website/.gitignore"
# append_file_to_file(gitignore_file_path, f"{os.getcwd()}/{project_name}/.gitignore")
# delete_file(gitignore_file_path)
commit_and_push(
"Initialized React", project_name, github_username, github_auth, directory=project_name,
)
@action_hook("github_actions", "web_frontend", "react")
def setup_actions():
project_name: str = Node.get_full_response()["metadata"]["name"]
github_username: str = Node.get_full_response()["github_credentials"]["username"]
github_auth: str = ""
if "password" in Node.get_full_response()["github_credentials"]:
github_auth = Node.get_full_response()["github_credentials"]["password"]
if "oauth_token" in Node.get_full_response()["github_credentials"]:
github_auth = Node.get_full_response()["github_credentials"]["oauth_token"]
copy_file(
f"{__assets_directory__}/react/nodejs.yml",
f"{os.getcwd()}/{project_name}/.github/workflows/nodejs.yml",
)
commit_and_push(
"Setup Github Actions", project_name, github_username, github_auth, directory=project_name,
)
| 39.517241 | 100 | 0.704188 | 289 | 2,292 | 5.224913 | 0.217993 | 0.060265 | 0.094702 | 0.163576 | 0.59404 | 0.50596 | 0.50596 | 0.50596 | 0.50596 | 0.37351 | 0 | 0 | 0.163613 | 2,292 | 57 | 101 | 40.210526 | 0.787689 | 0.085079 | 0 | 0.363636 | 0 | 0 | 0.276636 | 0.045867 | 0 | 0 | 0 | 0 | 0 | 1 | 0.045455 | false | 0.090909 | 0.159091 | 0 | 0.204545 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 |
e7964796b9ab80b4e2528d64eedc12992d2ed334 | 244 | py | Python | Estudos/110exercicios/Exercicios/ex064b.py | romuloferraz/Python | 2e20e7483cf9ea74b0b514f253034002bb56807f | [
"MIT"
] | null | null | null | Estudos/110exercicios/Exercicios/ex064b.py | romuloferraz/Python | 2e20e7483cf9ea74b0b514f253034002bb56807f | [
"MIT"
] | null | null | null | Estudos/110exercicios/Exercicios/ex064b.py | romuloferraz/Python | 2e20e7483cf9ea74b0b514f253034002bb56807f | [
"MIT"
] | null | null | null | num = cont = 0
s = 0
num = int(input('Digite um número [999 para PARAR]: '))
while num != 999:
s = s + num
cont += 1
num = int(input('Digite um número [999 para PARAR]: '))
print(f'Você digitou {cont} números e a soma deles é {s}')
| 27.111111 | 59 | 0.598361 | 43 | 244 | 3.395349 | 0.55814 | 0.09589 | 0.150685 | 0.232877 | 0.506849 | 0.506849 | 0.506849 | 0.506849 | 0.506849 | 0 | 0 | 0.065217 | 0.245902 | 244 | 8 | 60 | 30.5 | 0.728261 | 0 | 0 | 0.25 | 0 | 0 | 0.483607 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.125 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
e79b3c18a95ca266ee267d88b501327646e581de | 614 | py | Python | search/linear_search.py | thalysonrodrigues/data-structures | b3540f3115cc117f79085b5c7173e1a8d7845dc9 | [
"MIT"
] | 1 | 2021-03-16T19:59:28.000Z | 2021-03-16T19:59:28.000Z | search/linear_search.py | thalysonalexr/data-structures | b3540f3115cc117f79085b5c7173e1a8d7845dc9 | [
"MIT"
] | null | null | null | search/linear_search.py | thalysonalexr/data-structures | b3540f3115cc117f79085b5c7173e1a8d7845dc9 | [
"MIT"
] | null | null | null | def busca_linear_recursiva(elemento, l, idx=0):
if elemento == l[idx]:
return idx
if idx == len(l)-1:
return -1
return busca_linear_recursiva(elemento, l, idx + 1)
def busca_linear(elemento, l):
for i, e in enumerate(l):
if elemento == e:
return i
return -1
if __name__ == '__main__':
l = [44, 12, 43, 8, 99, 13, 1, -1, 4]
i = busca_linear_recursiva(int(input('Elemento: ')), l)
print('---- * LINEAR SEARCH * ----')
if i != -1:
print('Elemento encontrado! Posição %d.' % i)
else:
print('O elemento não está na lista.') | 26.695652 | 59 | 0.558632 | 88 | 614 | 3.727273 | 0.443182 | 0.137195 | 0.182927 | 0.170732 | 0.195122 | 0.195122 | 0 | 0 | 0 | 0 | 0 | 0.045662 | 0.286645 | 614 | 23 | 60 | 26.695652 | 0.703196 | 0 | 0 | 0.105263 | 0 | 0 | 0.172358 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.105263 | false | 0 | 0 | 0 | 0.368421 | 0.157895 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
e7b4bd1ed3947f14d23317feb8bbd170a4181fc5 | 335 | py | Python | Chapter5/py016.py | vztpv/Python-Study | a41e4e916cf264360ecdc3b59929246c672c87c4 | [
"MIT"
] | null | null | null | Chapter5/py016.py | vztpv/Python-Study | a41e4e916cf264360ecdc3b59929246c672c87c4 | [
"MIT"
] | null | null | null | Chapter5/py016.py | vztpv/Python-Study | a41e4e916cf264360ecdc3b59929246c672c87c4 | [
"MIT"
] | null | null | null | # 5-5 Problems
print(all([1, 2, abs(-3)-3]))
print(chr(ord('a')) == 'a')
x = [1, -2, 3, -5, 8, -3]
print(list(filter(lambda val: val > 0, x)))
x = hex(234)
print(int(x, 16))
x = [1, 2, 3, 4]
print(list(map(lambda a: a * 3, x)))
x = [-8, 2, 7, 5, -3, 5, 0, 1]
print(max(x) + min(x))
x = 17 / 3
print(round(x, 4)) | 17.631579 | 44 | 0.468657 | 71 | 335 | 2.211268 | 0.408451 | 0.038217 | 0.038217 | 0.050955 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.138889 | 0.247761 | 335 | 19 | 45 | 17.631579 | 0.484127 | 0.035821 | 0 | 0 | 0 | 0 | 0.006579 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.583333 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 2 |
e7c157fc1833580f9f4150cafbc927deaa86d6a5 | 722 | py | Python | data_management_scripts/group_age_data.py | skoskjei/ResNet_age_emotion | 40ded5f744f0110ecac452cb57c5a90626b8fb79 | [
"MIT"
] | null | null | null | data_management_scripts/group_age_data.py | skoskjei/ResNet_age_emotion | 40ded5f744f0110ecac452cb57c5a90626b8fb79 | [
"MIT"
] | null | null | null | data_management_scripts/group_age_data.py | skoskjei/ResNet_age_emotion | 40ded5f744f0110ecac452cb57c5a90626b8fb79 | [
"MIT"
] | null | null | null | import glob, os
import shutil
olddir = os.getcwd()
newdir = olddir + "\\face_age_add_age_and_emotion_done"
os.chdir(newdir)
for file in glob.glob("*.png"):
if file.startswith("072_") or file.startswith("073_") or file.startswith("074_") or file.startswith("075_") or file.startswith("076_") or file.startswith("077_") or file.startswith("078_"):
#change to 1
filenamesplit = file.split("_")
filenamept2 = filenamesplit[1]
filenamept3 = filenamesplit[2]
newfilename = "25" + "_" + str(filenamept2) + "_" + str(filenamept3)
destfile = olddir + "\\face_age_add_age_and_emotion_really_done_now_finito\\" + newfilename
shutil.move(file, destfile) | 40.111111 | 194 | 0.663435 | 89 | 722 | 5.101124 | 0.494382 | 0.215859 | 0.211454 | 0.070485 | 0.127753 | 0.127753 | 0.127753 | 0 | 0 | 0 | 0 | 0.051903 | 0.199446 | 722 | 18 | 195 | 40.111111 | 0.733564 | 0.015235 | 0 | 0 | 0 | 0 | 0.184438 | 0.129683 | 0.076923 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.153846 | 0 | 0.153846 | 0 | 0 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
e7c7b7d251f6586fc103736bb9561d3612819084 | 209 | py | Python | Crie um algoritmo que leia um numeor e mostre o seu dobro e seu triplo e raiz quadrada.py | Thiago251/Codigos_Python | 566be04310cd87b6df718746581eba0da2f0293d | [
"MIT"
] | null | null | null | Crie um algoritmo que leia um numeor e mostre o seu dobro e seu triplo e raiz quadrada.py | Thiago251/Codigos_Python | 566be04310cd87b6df718746581eba0da2f0293d | [
"MIT"
] | null | null | null | Crie um algoritmo que leia um numeor e mostre o seu dobro e seu triplo e raiz quadrada.py | Thiago251/Codigos_Python | 566be04310cd87b6df718746581eba0da2f0293d | [
"MIT"
] | null | null | null | n = int(input('Digite um numero: '))
print('O dobro de n é:', n**2 )
print('O triplo de n é: ', n ** 3 )
print('A raiz quadrada de n é:', n ** (1/2 ))
print('A raiz quadrada de n é {:.3f}' .format(n ** (1/2))) | 41.8 | 58 | 0.555024 | 44 | 209 | 2.636364 | 0.454545 | 0.103448 | 0.137931 | 0.12931 | 0.37931 | 0.37931 | 0.37931 | 0 | 0 | 0 | 0 | 0.041916 | 0.200957 | 209 | 5 | 58 | 41.8 | 0.652695 | 0 | 0 | 0 | 0 | 0 | 0.485714 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.8 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 2 |
e7d3e6b1568d90231951fbf8fa56f99f113dc472 | 997 | py | Python | heltour/tournament/migrations/0047_auto_20160802_2258.py | lenguyenthanh/heltour | 13018b1905539de0b273370a76f6aa1d1ebbb01a | [
"MIT"
] | null | null | null | heltour/tournament/migrations/0047_auto_20160802_2258.py | lenguyenthanh/heltour | 13018b1905539de0b273370a76f6aa1d1ebbb01a | [
"MIT"
] | null | null | null | heltour/tournament/migrations/0047_auto_20160802_2258.py | lenguyenthanh/heltour | 13018b1905539de0b273370a76f6aa1d1ebbb01a | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
# Generated by Django 1.9.7 on 2016-08-02 22:58
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('tournament', '0046_auto_20160802_2113'),
]
operations = [
migrations.AlterField(
model_name='round',
name='number',
field=models.PositiveIntegerField(verbose_name='round number'),
),
migrations.AlterField(
model_name='season',
name='start_date',
field=models.DateTimeField(blank=True, null=True),
),
migrations.AlterField(
model_name='team',
name='name',
field=models.CharField(max_length=255, verbose_name='team name'),
),
migrations.AlterField(
model_name='team',
name='number',
field=models.PositiveIntegerField(verbose_name='team number'),
),
]
| 27.694444 | 77 | 0.585757 | 97 | 997 | 5.845361 | 0.536082 | 0.141093 | 0.176367 | 0.204586 | 0.306878 | 0.306878 | 0.183422 | 0 | 0 | 0 | 0 | 0.049929 | 0.296891 | 997 | 35 | 78 | 28.485714 | 0.758916 | 0.067202 | 0 | 0.428571 | 1 | 0 | 0.118662 | 0.024811 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.071429 | 0 | 0.178571 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
99b4205d6f4167841d99deb57ea4a9a25aa6bcbb | 231 | py | Python | yt/frontends/gdf/api.py | aemerick/yt | 984484616d75c6d7603e71b9d45c5d617705a0e5 | [
"BSD-3-Clause-Clear"
] | null | null | null | yt/frontends/gdf/api.py | aemerick/yt | 984484616d75c6d7603e71b9d45c5d617705a0e5 | [
"BSD-3-Clause-Clear"
] | null | null | null | yt/frontends/gdf/api.py | aemerick/yt | 984484616d75c6d7603e71b9d45c5d617705a0e5 | [
"BSD-3-Clause-Clear"
] | null | null | null | from .data_structures import \
GDFGrid, \
GDFHierarchy, \
GDFDataset
from .fields import \
GDFFieldInfo
add_gdf_field = GDFFieldInfo.add_field
from .io import \
IOHandlerGDFHDF5
from . import tests
| 16.5 | 38 | 0.688312 | 24 | 231 | 6.458333 | 0.625 | 0.193548 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.005814 | 0.255411 | 231 | 13 | 39 | 17.769231 | 0.895349 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.4 | 0 | 0.4 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 2 |
99b5c95489cbab0d2154e8450efb039c6f06013a | 20,930 | py | Python | language_identification.py | honeybhardwaj/Language_Identification | 1b74f898be5402b0c1a13debf595736a3f57d7e7 | [
"MIT"
] | 4 | 2021-03-25T15:49:56.000Z | 2021-12-15T09:10:04.000Z | language_identification.py | honeybhardwaj/Language_Identification | 1b74f898be5402b0c1a13debf595736a3f57d7e7 | [
"MIT"
] | null | null | null | language_identification.py | honeybhardwaj/Language_Identification | 1b74f898be5402b0c1a13debf595736a3f57d7e7 | [
"MIT"
] | 3 | 2021-03-28T16:13:00.000Z | 2021-07-16T10:27:25.000Z | # -*- coding: utf-8 -*-
"""language_identification.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/14nWthI6ULAXAdK0KcmNdQiwa22c1Yk37
## Importing Libraries
"""
import warnings
warnings.filterwarnings("ignore")
from mpl_toolkits.mplot3d import Axes3D
from sklearn.preprocessing import StandardScaler
import matplotlib.pyplot as plt # plotting
import numpy as np
import seaborn as sns
import pandas as pd
import re
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score,confusion_matrix
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.preprocessing import LabelEncoder
"""## Loading Dataset"""
dataset=pd.read_csv("/content/drive/MyDrive/dataset.csv")
dataset.head()
# Distribution graphs (histogram/bar graph) of column data
def plotPerColumnDistribution(df, nGraphShown, nGraphPerRow):
nunique = df.nunique()
df = df[[col for col in df if nunique[col] > 1 and nunique[col] < 50]] # For displaying purposes, pick columns that have between 1 and 50 unique values
nRow, nCol = df.shape
columnNames = list(df)
nGraphRow = (nCol + nGraphPerRow - 1) / nGraphPerRow
plt.figure(num = None, figsize = (6 * nGraphPerRow, 8 * nGraphRow), dpi = 80, facecolor = 'w', edgecolor = 'k')
for i in range(min(nCol, nGraphShown)):
plt.subplot(nGraphRow, nGraphPerRow, i + 1)
columnDf = df.iloc[:, i]
if (not np.issubdtype(type(columnDf.iloc[0]), np.number)):
valueCounts = columnDf.value_counts()
valueCounts.plot.bar()
else:
columnDf.hist()
plt.ylabel('counts')
plt.xticks(rotation = 90)
plt.title(f'{columnNames[i]} (column {i})')
plt.tight_layout(pad = 1.0, w_pad = 1.0, h_pad = 1.0)
plt.show()
plotPerColumnDistribution(dataset, 10, 5)
"""## Data Preprocessing
this will be doing following:
* Splitting X and Y
* Encoding Y
* Cleaning and Lowering Text
"""
# Splitting X and Y
x,y = dataset["Text"],dataset["language"]
# Encoding Y
#encoder = LabelEncoder()
#y = encoder.fit_transform(y)
print(y[:10])
print(len(np.unique(y)))
# Cleaning and lowering text
def cleanLower(texts):
# This regular expression pattern means everything except alphabetical characters
pattern = "^[a-zA-Z]"
cleanText = []
for text in texts:
# re.sub(pattern) means replace everything with a space except alphabetical characters
cleanText.append(re.sub(pattern," ",text).lower())
return cleanText
x = cleanLower(x)
x[:4]
"""## test train splitting"""
#split the data into train and test set
from sklearn.model_selection import train_test_split
train_features, test_features, train_labels, test_labels = train_test_split(x, y, test_size=0.20, random_state=5)
print('lenght of training data = ',len(train_features))
print('lenght of test data = ', len(test_features))
"""## Feature Extraction"""
from sklearn.feature_extraction.text import*
from sklearn import preprocessing
from sklearn.preprocessing import LabelEncoder
#uni gram
uni_vector = CountVectorizer( strip_accents='unicode', analyzer='word', token_pattern=r'\w{1,}',
stop_words=None, ngram_range=(1,1), max_features=1000)
bag_of_words_uni = uni_vector.fit_transform(train_features)
#bigram
bi_vector = CountVectorizer( strip_accents='unicode', analyzer='word', token_pattern=r'\w{1,}',
stop_words=None, ngram_range=(2,2), max_features=1000)
bag_of_words_bi = bi_vector.fit_transform(train_features)
#trigram
tri_vector = CountVectorizer( strip_accents='unicode', analyzer='word', token_pattern=r'\w{1,}',
stop_words=None, ngram_range=(3,3), max_features=1000)
bag_of_words_tri = tri_vector.fit_transform(train_features)
#3chargram
char3_vector = CountVectorizer( strip_accents='unicode', analyzer='char', token_pattern=r'\w{1,}',
stop_words=None, ngram_range=(3,3), max_features=1000)
bag_of_words_char3 = char3_vector.fit_transform(train_features)
#4chargram
char4_vector = CountVectorizer( strip_accents='unicode', analyzer='char', token_pattern=r'\w{1,}',
stop_words=None, ngram_range=(4,4), max_features=1000)
bag_of_words_char4 = char4_vector.fit_transform(train_features)
#5chargram
char5_vector = CountVectorizer( strip_accents='unicode', analyzer='char', token_pattern=r'\w{1,}',
stop_words=None, ngram_range=(5,5), max_features=1000)
bag_of_words_char5 = char5_vector.fit_transform(train_features)
#6chargram
char6_vector = CountVectorizer( strip_accents='unicode', analyzer='char', token_pattern=r'\w{1,}',
stop_words=None, ngram_range=(6,6), max_features=1000)
bag_of_words_char6 = char6_vector.fit_transform(train_features)
#7chargram
char7_vector = CountVectorizer( strip_accents='unicode', analyzer='char', token_pattern=r'\w{1,}',
stop_words=None, ngram_range=(7,7), max_features=1000)
bag_of_words_char7 = char7_vector.fit_transform(train_features)
#8chargram
char8_vector = CountVectorizer( strip_accents='unicode', analyzer='char', token_pattern=r'\w{1,}',
stop_words=None, ngram_range=(1,1), max_features=1000)
bag_of_words_char8 = char8_vector.fit_transform(train_features)
#9chargram
char9_vector = CountVectorizer( strip_accents='unicode', analyzer='char', token_pattern=r'\w{1,}',
stop_words=None, ngram_range=(9,9), max_features=1000)
bag_of_words_char9 = char9_vector.fit_transform(train_features)
#10chargram
char10_vector = CountVectorizer( strip_accents='unicode', analyzer='char', token_pattern=r'\w{1,}',
stop_words=None, ngram_range=(10,10), max_features=1000)
bag_of_words_char10 = char10_vector.fit_transform(train_features)
# Get feature names
uni_feature_names = uni_vector.get_feature_names()
bi_feature_names = bi_vector.get_feature_names()
tri_feature_names = tri_vector.get_feature_names()
char3_feature_names = char3_vector.get_feature_names()
char4_feature_names = char4_vector.get_feature_names()
char5_feature_names = char5_vector.get_feature_names()
char6_feature_names = char6_vector.get_feature_names()
char7_feature_names = char7_vector.get_feature_names()
char8_feature_names = char8_vector.get_feature_names()
char9_feature_names = char9_vector.get_feature_names()
char10_feature_names = char10_vector.get_feature_names()
uni_train_features=pd.DataFrame(bag_of_words_uni.toarray(), columns=uni_feature_names)
uni_train_features[:5]
bi_train_features=pd.DataFrame(bag_of_words_bi.toarray(), columns=bi_feature_names)
tri_train_features=pd.DataFrame(bag_of_words_tri.toarray(), columns=tri_feature_names)
char3_train_features=pd.DataFrame(bag_of_words_char3.toarray(), columns=char3_feature_names)
char4_train_features=pd.DataFrame(bag_of_words_char4.toarray(), columns=char4_feature_names)
char5_train_features=pd.DataFrame(bag_of_words_char5.toarray(), columns=char5_feature_names)
char6_train_features=pd.DataFrame(bag_of_words_char6.toarray(), columns=char6_feature_names)
char7_train_features=pd.DataFrame(bag_of_words_char7.toarray(), columns=char7_feature_names)
char8_train_features=pd.DataFrame(bag_of_words_char8.toarray(), columns=char8_feature_names)
char9_train_features=pd.DataFrame(bag_of_words_char9.toarray(), columns=char9_feature_names)
char10_train_features=pd.DataFrame(bag_of_words_char10.toarray(), columns=char10_feature_names)
"""## training data on ml models
* Random Forest
* Linear SVC
* Logistic Regression
"""
from sklearn.ensemble import RandomForestClassifier
#apply RandomForestClassifier on train dataset
rfc_uni = RandomForestClassifier()
rfc_uni.fit(uni_train_features, train_labels);
rfc_bi = RandomForestClassifier()
rfc_bi.fit(bi_train_features, train_labels);
rfc_tri = RandomForestClassifier()
rfc_tri.fit(tri_train_features, train_labels);
rfc_char3 = RandomForestClassifier()
rfc_char3.fit(char3_train_features, train_labels);
rfc_char4 = RandomForestClassifier()
rfc_char4.fit(char4_train_features, train_labels);
rfc_char5 = RandomForestClassifier()
rfc_char5.fit(char5_train_features, train_labels);
rfc_char6 = RandomForestClassifier()
rfc_char6.fit(char6_train_features, train_labels);
rfc_char7 = RandomForestClassifier()
rfc_char7.fit(char7_train_features, train_labels);
rfc_char8 = RandomForestClassifier()
rfc_char8.fit(char8_train_features, train_labels);
rfc_char9 = RandomForestClassifier()
rfc_char9.fit(char9_train_features, train_labels);
rfc_char10 = RandomForestClassifier()
rfc_char10.fit(char10_train_features, train_labels);
from sklearn.svm import LinearSVC
#apply LinearSVC() on train dataset
lsvc_uni = LinearSVC()
lsvc_uni.fit(uni_train_features, train_labels);
lsvc_bi = LinearSVC()
lsvc_bi.fit(bi_train_features, train_labels);
lsvc_tri = LinearSVC()
lsvc_tri.fit(tri_train_features, train_labels);
lsvc_char3 = LinearSVC()
lsvc_char3.fit(char3_train_features, train_labels);
lsvc_char4 = LinearSVC()
lsvc_char4.fit(char4_train_features, train_labels);
lsvc_char5 = LinearSVC()
lsvc_char5.fit(char5_train_features, train_labels);
lsvc_char6 = LinearSVC()
lsvc_char6.fit(char6_train_features, train_labels);
lsvc_char7 = LinearSVC()
lsvc_char7.fit(char7_train_features, train_labels);
lsvc_char8 = LinearSVC()
lsvc_char8.fit(char8_train_features, train_labels);
lsvc_char9 = LinearSVC()
lsvc_char9.fit(char9_train_features, train_labels);
lsvc_char10 = LinearSVC()
lsvc_char10.fit(char10_train_features, train_labels);
from sklearn.linear_model import LogisticRegression
#apply LogisticRegression() on train dataset
lr_uni = LogisticRegression()
lr_uni.fit(uni_train_features, train_labels);
lr_bi = LogisticRegression()
lr_bi.fit(bi_train_features, train_labels);
lr_tri = LogisticRegression()
lr_tri.fit(tri_train_features, train_labels);
lr_char3 = LogisticRegression()
lr_char3.fit(char3_train_features, train_labels);
lr_char4 = LogisticRegression()
lr_char4.fit(char4_train_features, train_labels);
lr_char5 = LogisticRegression()
lr_char5.fit(char5_train_features, train_labels);
lr_char6 = LogisticRegression()
lr_char6.fit(char6_train_features, train_labels);
lr_char7 = LogisticRegression()
lr_char7.fit(char7_train_features, train_labels);
lr_char8 = LogisticRegression()
lr_char8.fit(char8_train_features, train_labels);
lr_char9 = LogisticRegression()
lr_char9.fit(char9_train_features, train_labels);
lr_char10 = LogisticRegression()
lr_char10.fit(char10_train_features, train_labels);
"""## testing model"""
uni_test_features = uni_vector.transform(test_features)
uni_test_features=pd.DataFrame(uni_test_features.toarray(), columns=uni_feature_names)
uni_test_features[:5]
bi_test_features = bi_vector.transform(test_features)
bi_test_features=pd.DataFrame(bi_test_features.toarray(), columns=bi_feature_names)
tri_test_features = tri_vector.transform(test_features)
tri_test_features=pd.DataFrame(tri_test_features.toarray(), columns=tri_feature_names)
char3_test_features = char3_vector.transform(test_features)
char3_test_features=pd.DataFrame(char3_test_features.toarray(), columns=char3_feature_names)
char4_test_features = char4_vector.transform(test_features)
char4_test_features=pd.DataFrame(char4_test_features.toarray(), columns=char4_feature_names)
char5_test_features = char5_vector.transform(test_features)
char5_test_features=pd.DataFrame(char5_test_features.toarray(), columns=char5_feature_names)
char6_test_features = char6_vector.transform(test_features)
char6_test_features=pd.DataFrame(char6_test_features.toarray(), columns=char6_feature_names)
char7_test_features = char7_vector.transform(test_features)
char7_test_features=pd.DataFrame(char7_test_features.toarray(), columns=char7_feature_names)
char8_test_features = char8_vector.transform(test_features)
char8_test_features=pd.DataFrame(char8_test_features.toarray(), columns=char8_feature_names)
char9_test_features = char9_vector.transform(test_features)
char9_test_features=pd.DataFrame(char9_test_features.toarray(), columns=char9_feature_names)
char10_test_features = char10_vector.transform(test_features)
char10_test_features=pd.DataFrame(char10_test_features.toarray(), columns=char10_feature_names)
"""## Evaluation using test data on ml algorithms"""
from sklearn.metrics import accuracy_score
# random forest
predictions_uni_rfc = rfc_uni.predict(uni_test_features) #prediction
uni_rfc = accuracy_score(test_labels, predictions_uni_rfc) #accuracy
predictions_bi_rfc = rfc_bi.predict(bi_test_features) #prediction
bi_rfc = accuracy_score(test_labels, predictions_bi_rfc) #accuracy
predictions_tri_rfc = rfc_tri.predict(tri_test_features) #prediction
tri_rfc = accuracy_score(test_labels, predictions_tri_rfc) #accuracy
predictions_char3_rfc = rfc_char3.predict(char3_test_features) #prediction
char3_rfc = accuracy_score(test_labels, predictions_char3_rfc) #accuracy
predictions_char4_rfc = rfc_char4.predict(char4_test_features) #prediction
char4_rfc = accuracy_score(test_labels, predictions_char4_rfc) #accuracy
predictions_char5_rfc = rfc_char5.predict(char5_test_features) #prediction
char5_rfc = accuracy_score(test_labels, predictions_char5_rfc) #accuracy
predictions_char6_rfc = rfc_char6.predict(char6_test_features) #prediction
char6_rfc = accuracy_score(test_labels, predictions_char6_rfc) #accuracy
predictions_char7_rfc = rfc_char7.predict(char7_test_features) #prediction
char7_rfc = accuracy_score(test_labels, predictions_char7_rfc) #accuracy
predictions_char8_rfc = rfc_char8.predict(char8_test_features) #prediction
char8_rfc = accuracy_score(test_labels, predictions_char8_rfc) #accuracy
predictions_char9_rfc = rfc_char9.predict(char9_test_features) #prediction
char9_rfc = accuracy_score(test_labels, predictions_char9_rfc) #accuracy
predictions_char10_rfc = rfc_char10.predict(char10_test_features) #prediction
char10_rfc = accuracy_score(test_labels, predictions_char10_rfc) #accuracy
# linear SVC
predictions_uni_lsvc= lsvc_uni.predict(uni_test_features) #prediction
uni_lsvc = accuracy_score(test_labels, predictions_uni_lsvc) #accuracy
predictions_bi_lsvc = lsvc_bi.predict(bi_test_features) #prediction
bi_lsvc = accuracy_score(test_labels, predictions_bi_lsvc) #accuracy
predictions_tri_lsvc = lsvc_tri.predict(tri_test_features) #prediction
tri_lsvc = accuracy_score(test_labels, predictions_tri_lsvc) #accuracy
predictions_char3_lsvc = lsvc_char3.predict(char3_test_features) #prediction
char3_lsvc = accuracy_score(test_labels, predictions_char3_lsvc) #accuracy
predictions_char4_lsvc = lsvc_char4.predict(char4_test_features) #prediction
char4_lsvc = accuracy_score(test_labels, predictions_char4_lsvc) #accuracy
predictions_char5_lsvc = lsvc_char5.predict(char5_test_features) #prediction
char5_lsvc = accuracy_score(test_labels, predictions_char5_lsvc) #accuracy
predictions_char6_lsvc = lsvc_char6.predict(char6_test_features) #prediction
char6_lsvc = accuracy_score(test_labels, predictions_char6_lsvc) #accuracy
predictions_char7_lsvc = lsvc_char7.predict(char7_test_features) #prediction
char7_lsvc = accuracy_score(test_labels, predictions_char7_lsvc) #accuracy
predictions_char8_lsvc = lsvc_char8.predict(char8_test_features) #prediction
char8_lsvc = accuracy_score(test_labels, predictions_char8_lsvc) #accuracy
predictions_char9_lsvc = lsvc_char9.predict(char9_test_features) #prediction
char9_lsvc = accuracy_score(test_labels, predictions_char9_lsvc) #accuracy
predictions_char10_lsvc = lsvc_char10.predict(char10_test_features) #prediction
char10_lsvc = accuracy_score(test_labels, predictions_char10_lsvc) #accuracy
# Logistic regressiom
predictions_uni_lr = lr_uni.predict(uni_test_features) #prediction
uni_lr = accuracy_score(test_labels, predictions_uni_lr) #accuracy
predictions_bi_lr = lr_bi.predict(bi_test_features) #prediction
bi_lr = accuracy_score(test_labels, predictions_bi_lr) #accuracy
predictions_tri_lr = lr_tri.predict(tri_test_features) #prediction
tri_lr = accuracy_score(test_labels, predictions_tri_lr) #accuracy
predictions_char3_lr = lr_char3.predict(char3_test_features) #prediction
char3_lr = accuracy_score(test_labels, predictions_char3_lr) #accuracy
predictions_char4_lr = lr_char4.predict(char4_test_features) #prediction
char4_lr = accuracy_score(test_labels, predictions_char4_lr) #accuracy
predictions_char5_lr = lr_char5.predict(char5_test_features) #prediction
char5_lr = accuracy_score(test_labels, predictions_char5_lr) #accuracy
predictions_char6_lr = lr_char6.predict(char6_test_features) #prediction
char6_lr = accuracy_score(test_labels, predictions_char6_lr) #accuracy
predictions_char7_lr = lr_char7.predict(char7_test_features) #prediction
char7_lr = accuracy_score(test_labels, predictions_char7_lr) #accuracy
predictions_char8_lr = lr_char8.predict(char8_test_features) #prediction
char8_lr = accuracy_score(test_labels, predictions_char8_lr) #accuracy
predictions_char9_lr = lr_char9.predict(char9_test_features) #prediction
char9_lr = accuracy_score(test_labels, predictions_char9_lr) #accuracy
predictions_char10_lr = lr_char10.predict(char10_test_features) #prediction
char10_lr = accuracy_score(test_labels, predictions_char10_lr) #accuracy
"""## selection of best model"""
!pip install prettytable
from prettytable import PrettyTable
from astropy.table import Table, Column
Model_Table = PrettyTable()
Model_Table.field_names = [" ", " Random forest Classififier ", " Linear SVC "," Logistic Regression "]
Model_Table.add_row([" Uni Gram ", round(uni_rfc,2),round(uni_lsvc,2),round(uni_lr,2)])
Model_Table.add_row([" Bi Gram ", round(bi_rfc,2),round(bi_lsvc,2),round(bi_lr,2)])
Model_Table.add_row([" Tri Gram ", round(tri_rfc,2),round(tri_lsvc,2),round(tri_lr,2)])
Model_Table.add_row([" 3 Char Gram ", round(char3_rfc,2),round(char3_lsvc,2),round(char3_lr,2)])
Model_Table.add_row([" 4 Char Gram ", round(char4_rfc,2),round(char4_lsvc,2),round(char4_lr,2)])
Model_Table.add_row([" 5 Char Gram ", round(char5_rfc,2),round(char5_lsvc,2),round(char5_lr,2)])
Model_Table.add_row([" 6 Char Gram ", round(char6_rfc,2),round(char6_lsvc,2),round(char6_lr,2)])
Model_Table.add_row([" 7 Char Gram ", round(char7_rfc,2),round(char7_lsvc,2),round(char7_lr,2)])
Model_Table.add_row([" 8 Char Gram ", round(char8_rfc,2),round(char8_lsvc,2),round(char8_lr,2)])
Model_Table.add_row([" 9 Char Gram ", round(char9_rfc,2),round(char9_lsvc,2),round(char9_lr,2)])
Model_Table.add_row([" 10 Char Gram ", round(char10_rfc,2),round(char10_lsvc,2),round(char10_lr,2)])
print("Detailed performance of all models:")
print(Model_Table)
Best_Model = PrettyTable()
Best_Model.field_names = [" ", " Random forest Classififier ", " Linear SVC "," Logistic Regression "]
Best_Model.add_row([" Uni Gram ", round(uni_rfc,2),round(uni_lsvc,2),round(uni_lr,2)])
Best_Model.add_row([" 3 Char Gram ", round(char3_rfc,2),round(char3_lsvc,2),round(char3_lr,2)])
Best_Model.add_row([" 8 Char Gram ", round(char8_rfc,2),round(char8_lsvc,2),round(char8_lr,2)])
print("Best Model")
print(Best_Model)
"""## application phase saving model"""
features = uni_vector.transform(x)
target=y
#apply random forest on train dataset
model=rfc_uni.fit(features, target);
import pickle
filename = 'unigram_model.sav'
pickle.dump(model, open(filename, 'wb'))
| 41.86 | 155 | 0.740325 | 2,712 | 20,930 | 5.350664 | 0.107301 | 0.066157 | 0.044518 | 0.054579 | 0.540969 | 0.495831 | 0.318035 | 0.119633 | 0.113431 | 0.098132 | 0 | 0.031586 | 0.165026 | 20,930 | 499 | 156 | 41.943888 | 0.798753 | 0.066269 | 0 | 0.026667 | 1 | 0 | 0.040313 | 0.001811 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0.076667 | null | null | 0.026667 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
99c740c864ac8f17dc5a2661453594e375f82b2a | 951 | py | Python | main.py | SupernovaXTS/DylanRowanEV3 | 4a0ad689efcc284df4f5b2aae65934b7ca266e52 | [
"MIT"
] | null | null | null | main.py | SupernovaXTS/DylanRowanEV3 | 4a0ad689efcc284df4f5b2aae65934b7ca266e52 | [
"MIT"
] | null | null | null | main.py | SupernovaXTS/DylanRowanEV3 | 4a0ad689efcc284df4f5b2aae65934b7ca266e52 | [
"MIT"
] | null | null | null | #!/usr/bin/env pybricks-micropython
from pybricks.hubs import EV3Brick
from pybricks.ev3devices import (Motor, TouchSensor, ColorSensor,
InfraredSensor, UltrasonicSensor, GyroSensor)
from pybricks.parameters import Port, Stop, Direction, Button, Color
from pybricks.tools import wait, StopWatch, DataLog
from pybricks.robotics import DriveBase
from pybricks.media.ev3dev import SoundFile, ImageFile
# This program requires LEGO EV3 MicroPython v2.0 or higher.
# Click "Open user guide" on the EV3 extension tab for more information.
# Create your objects here.
ev3 = EV3Brick()
# Write your program here.
US = UltrasonicSensor(Port.S1)
LeftMotor = Motor(port.A, positive_direction=Direction.CLOCKWISE, gears=None)
RightMotor = Motor(port.B, positive_direction=Direction.CLOCKWISE, gears=None)
drive = Drivebase(LeftMotor,RightMotor,60,200)
for x in range(4)
drive.straight(1000)
drive.stop()
drive.turn(90) | 35.222222 | 78 | 0.767613 | 123 | 951 | 5.918699 | 0.634146 | 0.098901 | 0.071429 | 0.096154 | 0.120879 | 0.120879 | 0 | 0 | 0 | 0 | 0 | 0.02716 | 0.148265 | 951 | 27 | 79 | 35.222222 | 0.871605 | 0.226078 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0.375 | null | null | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 2 |
99cedaac536f56fed7c80a3dae488f31828d8e72 | 158 | py | Python | Meus_dessafios/Exercicios2021/ex005.py | DiegoSilvaHoffmann/Curso-de-Python | 62824bbd3ed42b256fda77acd49536ec7cf23b29 | [
"MIT"
] | null | null | null | Meus_dessafios/Exercicios2021/ex005.py | DiegoSilvaHoffmann/Curso-de-Python | 62824bbd3ed42b256fda77acd49536ec7cf23b29 | [
"MIT"
] | null | null | null | Meus_dessafios/Exercicios2021/ex005.py | DiegoSilvaHoffmann/Curso-de-Python | 62824bbd3ed42b256fda77acd49536ec7cf23b29 | [
"MIT"
] | null | null | null | n1 = int(input('Digite qualquer numero: '))
a = n1 - 1
p = n1 + 1
print('O numero escolhido é {}, seu anterior é {}, e seu posterior é {}.'.format(n1, a, p))
| 31.6 | 91 | 0.607595 | 28 | 158 | 3.428571 | 0.642857 | 0.0625 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.047619 | 0.202532 | 158 | 4 | 92 | 39.5 | 0.714286 | 0 | 0 | 0 | 0 | 0 | 0.563291 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.25 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
99d3be44aaba7542cb9be61be07abe0d24a85036 | 1,049 | py | Python | python/challenge_3/tests/test_ch3.py | star-fangled-nut/ui-automation-week | c177dc3a13bed5a88764141b82c38a53bb50e796 | [
"Apache-2.0"
] | 4 | 2021-02-01T13:10:16.000Z | 2021-04-14T19:56:53.000Z | python/challenge_3/tests/test_ch3.py | star-fangled-nut/ui-automation-week | c177dc3a13bed5a88764141b82c38a53bb50e796 | [
"Apache-2.0"
] | null | null | null | python/challenge_3/tests/test_ch3.py | star-fangled-nut/ui-automation-week | c177dc3a13bed5a88764141b82c38a53bb50e796 | [
"Apache-2.0"
] | 6 | 2021-02-07T20:44:16.000Z | 2021-02-23T17:12:00.000Z | """ Welcome to UI Automation Challenge 3
For this challenge the focus is improving the assertion for an existing
UI automation test. Rather than asserting on the DOM's state, update the
the test below to do a visual check of the page. Once you've completed
the sample check. Create your own example check.
> Remember, Pylenium is just a wrapper of Selenium, so you already have access to Selenium!
"""
import pytest
from pylenium.driver import Pylenium
from python.challenge_3.pages.home_page import HomePage
@pytest.fixture
def home(py):
py.visit("https://automationintesting.online/");
return HomePage(py)
def test_check_the_home_page_data(home: HomePage):
img_url = home.get_hotel_logo().get_attribute('src')
assert "https://www.mwtestconsultancy.co.uk/img/rbp-logo.png" == img_url
assert home.get_room_images().should().have_length(1)
assert home.get_map_image_count().should().have_length(28)
def test_your_turn(py: Pylenium, home: HomePage):
""" Create your own demonstration of a visual check """
pass
| 33.83871 | 91 | 0.759771 | 164 | 1,049 | 4.731707 | 0.560976 | 0.027062 | 0.030928 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.005599 | 0.148713 | 1,049 | 30 | 92 | 34.966667 | 0.863382 | 0.42326 | 0 | 0 | 0 | 0 | 0.152284 | 0 | 0 | 0 | 0 | 0 | 0.214286 | 1 | 0.214286 | false | 0.071429 | 0.214286 | 0 | 0.5 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 |
99d8e0ee506f27621ae6d02cd86373d7ec069b49 | 87 | py | Python | uri_juego/punto1011.py | SebasBaquero/taller1-algoritmo | 950cfd8bd8541cd9108eb28f52b8b098e044b408 | [
"MIT"
] | null | null | null | uri_juego/punto1011.py | SebasBaquero/taller1-algoritmo | 950cfd8bd8541cd9108eb28f52b8b098e044b408 | [
"MIT"
] | null | null | null | uri_juego/punto1011.py | SebasBaquero/taller1-algoritmo | 950cfd8bd8541cd9108eb28f52b8b098e044b408 | [
"MIT"
] | null | null | null | r= int(input())
pi= 3.14159
sphere= (4/3)* pi* pow(r,3)
print("VOLUME = %.3f" %sphere)
| 17.4 | 30 | 0.586207 | 17 | 87 | 3 | 0.705882 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.133333 | 0.137931 | 87 | 4 | 31 | 21.75 | 0.546667 | 0 | 0 | 0 | 0 | 0 | 0.149425 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.25 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
99e04192f3d30576e05945c5227712f7bbb3b09d | 535 | py | Python | pysql/constants/core/constraints.py | jha-hitesh/pysql | ad7c7e4e7e65a97e4dc15cda395678e0c09b02ab | [
"MIT"
] | null | null | null | pysql/constants/core/constraints.py | jha-hitesh/pysql | ad7c7e4e7e65a97e4dc15cda395678e0c09b02ab | [
"MIT"
] | null | null | null | pysql/constants/core/constraints.py | jha-hitesh/pysql | ad7c7e4e7e65a97e4dc15cda395678e0c09b02ab | [
"MIT"
] | null | null | null | class CoreConstraintConstants:
core_constraint_slots = (
"table", "constraint_name", "constraint_definition",
"UNIQUE", "PRIMARY_KEY", "FOREIGN_KEY", "REFERENCES",
"CHECK", "DEFAULT", "FOR"
)
core_constraint_default_values = {
"table": None,
"constraint_name": None,
"constraint_definition": "",
"UNIQUE": (),
"PRIMARY_KEY": (),
"FOREIGN_KEY": None,
"REFERENCES": None,
"CHECK": (),
"DEFAULT": None,
"FOR": None
}
| 26.75 | 61 | 0.543925 | 43 | 535 | 6.465116 | 0.418605 | 0.100719 | 0.18705 | 0.23741 | 0.330935 | 0.330935 | 0.330935 | 0 | 0 | 0 | 0 | 0 | 0.300935 | 535 | 19 | 62 | 28.157895 | 0.743316 | 0 | 0 | 0 | 0 | 0 | 0.35206 | 0.078652 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0.166667 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
99e469f0bd7e1ee843301029a9f284f53cceeed1 | 3,226 | py | Python | headlock/address_space/__init__.py | mrh1997/headlock | 720ede7e02681d6466b27ae7fb3958ef8c4a238c | [
"MIT"
] | 2 | 2017-11-09T13:49:57.000Z | 2020-03-07T01:29:37.000Z | headlock/address_space/__init__.py | mrh1997/headlock | 720ede7e02681d6466b27ae7fb3958ef8c4a238c | [
"MIT"
] | 4 | 2017-12-22T12:27:34.000Z | 2020-03-31T07:42:07.000Z | headlock/address_space/__init__.py | mrh1997/headlock | 720ede7e02681d6466b27ae7fb3958ef8c4a238c | [
"MIT"
] | null | null | null | """
This is for headlock internal use only!
"""
from typing import Tuple, Callable
import abc
from collections.abc import ByteString
class MemoryManagementError(Exception):
"""
This exception occurs, when if memory allocation/release failed.
"""
class AddressSpace:
"""
An address space provides an interface to running C code at ABI (not API!)
layer.
This class is only the abstract base class. Descendants have to implement
the communication between this python process/machine and some specific
kind of "running code" (i.e. an OS user process, an OS kernel or an
embedded system running on a remote machine).
This class is not responsible to instanciate C code or stop it!
The the code has to be loaded somewhere else and a handle/ID has to be
passed to the constructor of the subclass.
"""
def __init__(self):
self.bridgepool = {}
def _register_memory_block(self, address, len):
pass
@abc.abstractmethod
def find_memory_block(self, address:int) -> Tuple[int, int]:
"""
returns the start address and the length of the memory block which
contains this address. raises ValueError if no containing memory block
exists
"""
@abc.abstractmethod
def read_memory(self, address:int, length:int) -> bytes:
"""
Reads a specific amount of Memory (in bytes) of the address space.
The caller has to ensure that the specified memory range is valid,
otherwise the connected process could crash
"""
@abc.abstractmethod
def write_memory(self, address:int, data:ByteString):
"""
Writes a specific amount of Memory (in bytes) to the address space.
The caller has to ensure that the specified memory range is valid,
otherwise the connected process could crash
"""
@abc.abstractmethod
def alloc_memory(self, length:int) -> int:
"""
Allocated length bytes of contiguous memory and returns a reference to
it.
"""
@abc.abstractmethod
def get_symbol_adr(self, symbol_name:str) -> int:
"""
returns the address of a specific symbol.
Symbol may be a global variable or a function.
"""
@abc.abstractmethod
def get_symbol_name(self, adr:int) -> str:
"""
returns the name of a symbol or raises ValueError is adr does not
refer to a valid C symbol
"""
@abc.abstractmethod
def invoke_c_func(self, func_adr:int, c_sig:str,
args_adr:int, retval_adr:int) -> bytes:
"""
invokes a piece of C code via the bridge for signature of name
"c_sig".
"""
@abc.abstractmethod
def create_c_callback(self, c_sig:str,
pyfunc:Callable[[int, int], None]) -> int:
"""
Creates a new C function pointer of signature 'c_sig'.
Everytime this function is called, the call is bridged and
forwarded to pyfunc.
Returns the address of the created C callback.
"""
@abc.abstractmethod
def close(self):
"""
Close the connection to the addressspace.
""" | 31.320388 | 78 | 0.641042 | 426 | 3,226 | 4.788732 | 0.375587 | 0.075 | 0.088235 | 0.021569 | 0.182353 | 0.153922 | 0.153922 | 0.12451 | 0.12451 | 0.12451 | 0 | 0 | 0.287973 | 3,226 | 103 | 79 | 31.320388 | 0.888115 | 0.520769 | 0 | 0.310345 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.37931 | false | 0.034483 | 0.103448 | 0 | 0.551724 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2 |
99e72c9ddc9461817e32a7f394cb94ec115be553 | 67 | py | Python | cms/__init__.py | umarmughal824/bootcamp-ecommerce | 681bcc788a66867b8f240790c0ed33680b73932b | [
"BSD-3-Clause"
] | 2 | 2018-06-20T19:37:03.000Z | 2021-01-06T09:51:40.000Z | cms/__init__.py | mitodl/bootcamp-ecommerce | ba7d6aefe56c6481ae2a5afc84cdd644538b6d50 | [
"BSD-3-Clause"
] | 1,226 | 2017-02-23T14:52:28.000Z | 2022-03-29T13:19:54.000Z | cms/__init__.py | umarmughal824/bootcamp-ecommerce | 681bcc788a66867b8f240790c0ed33680b73932b | [
"BSD-3-Clause"
] | 3 | 2017-03-20T03:51:27.000Z | 2021-03-19T15:54:31.000Z | """Initialize cms app"""
default_app_config = "cms.apps.CMSConfig"
| 22.333333 | 41 | 0.746269 | 9 | 67 | 5.333333 | 0.777778 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.089552 | 67 | 2 | 42 | 33.5 | 0.786885 | 0.268657 | 0 | 0 | 0 | 0 | 0.418605 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
99f07fca2c855b566511a0147923614aa1a1eac4 | 152 | py | Python | scheduler/app.py | zj-myidea/MYIDEA | 901389a779329603d141f0641c8d2bae423f1d6b | [
"BSD-2-Clause"
] | null | null | null | scheduler/app.py | zj-myidea/MYIDEA | 901389a779329603d141f0641c8d2bae423f1d6b | [
"BSD-2-Clause"
] | null | null | null | scheduler/app.py | zj-myidea/MYIDEA | 901389a779329603d141f0641c8d2bae423f1d6b | [
"BSD-2-Clause"
] | null | null | null | from agent import Agent
if __name__=='__main__':
agent = Agent()
try:
agent.start()
except Exception as e:
agent.shutdown() | 19 | 26 | 0.605263 | 18 | 152 | 4.666667 | 0.722222 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.289474 | 152 | 8 | 27 | 19 | 0.777778 | 0 | 0 | 0 | 0 | 0 | 0.052288 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.142857 | 0 | 0.142857 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
820b292abf75bb61e657c0cb248e9945a582ab26 | 1,526 | py | Python | categorical_embedder/embedders/core/vae/concrete/concrete_utils.py | erelcan/categorical-embedder | 376b8779500af2aa459c879f8e525f2ef25d6b31 | [
"Apache-2.0"
] | 3 | 2020-12-19T10:52:58.000Z | 2021-06-08T09:06:44.000Z | ts_embedder/embedders/core/vae/concrete/concrete_utils.py | erelcan/ts-embedder | 2fe73c70aa8a7bb8a232b3a66730b55d30db4694 | [
"Apache-2.0"
] | null | null | null | ts_embedder/embedders/core/vae/concrete/concrete_utils.py | erelcan/ts-embedder | 2fe73c70aa8a7bb8a232b3a66730b55d30db4694 | [
"Apache-2.0"
] | null | null | null | from keras import backend as K
def compute_kl_normal(z_mean, z_log_var):
# KL divergence between N(0,1) and N(z_mean, exp(z_log_var))
kl_per_sample = 0.5 * (K.sum(K.square(z_mean) + K.exp(z_log_var) - 1 - z_log_var, axis=1))
return K.mean(kl_per_sample)
def compute_kl_discrete(distributions):
# KL divergence between a uniform distribution over distributions of the categories.
# Re-consider whether you need a modified version of KL-div for ELBO!
num_of_categories = K.int_shape(distributions)[1]
dist_sum = K.sum(distributions * K.log(K.constant(1.0 / num_of_categories) + K.epsilon()), axis=1)
dist_neg_entropy = K.sum(distributions * K.log(distributions + K.epsilon()), axis=1)
return K.mean(dist_neg_entropy - dist_sum)
def sample_concrete(alpha, temperature):
# Sample from a concrete distribution given alpha and temperature
uniform = K.random_uniform(shape=K.shape(alpha))
gumbel = - K.log(- K.log(uniform + K.epsilon()) + K.epsilon())
logits = (K.log(alpha + K.epsilon()) + gumbel) / temperature
return K.softmax(logits)
def sample_normal(z_mean, z_log_var):
# Sample from a normal distribution with mean z_mean and variance z_log_var
epsilon = K.random_normal(shape=K.shape(z_mean), mean=0, stddev=1)
return z_mean + K.exp(z_log_var / 2) * epsilon
def concrete_sampler(temperature=0.1):
return lambda alpha: sample_concrete(alpha, temperature)
def normal_sampler():
return lambda z_tuple: sample_normal(z_tuple[0], z_tuple[1])
| 39.128205 | 102 | 0.722805 | 250 | 1,526 | 4.208 | 0.28 | 0.03327 | 0.046578 | 0.028517 | 0.134981 | 0.064639 | 0.030418 | 0 | 0 | 0 | 0 | 0.014085 | 0.162516 | 1,526 | 38 | 103 | 40.157895 | 0.809077 | 0.227392 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.285714 | false | 0 | 0.047619 | 0.095238 | 0.619048 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2 |
8214c4772f2b4cb0fd774778e36319286f3ba0db | 5,569 | py | Python | pythonlibs/mantis/trade/command.py | adoggie/Tibet.6 | 3c53060edafd80b9c4dafa10699a68d86a410c66 | [
"MIT"
] | 22 | 2019-10-28T07:28:12.000Z | 2022-03-19T15:36:41.000Z | pythonlibs/mantis/trade/command.py | adoggie/Tibet.6 | 3c53060edafd80b9c4dafa10699a68d86a410c66 | [
"MIT"
] | 1 | 2019-11-07T04:54:14.000Z | 2019-11-07T07:12:48.000Z | pythonlibs/mantis/trade/command.py | adoggie/Tibet.6 | 3c53060edafd80b9c4dafa10699a68d86a410c66 | [
"MIT"
] | 13 | 2019-10-28T07:29:07.000Z | 2021-11-03T06:53:12.000Z | # coding: utf-8
from vnpy.trader.vtObject import *
from mantis.fundamental.flask.webapi import CallReturn
# class Command(object):
# def __init__(self,name):
# self.name = name
class StartTradeAdapter(object):
"""请求TradeAdapter服务启动
场景： 调度服务器或者runner请求launcher启动tradeAdapter服务进程
"""
NAME = 'start_trade_adapter'
def __init__(self):
pass
class KeepAlive(object):
"""请求指定服务器保持运行，服务 A依赖B的运行，A定时发送此消息到B系统，B接收到保持自己服务器运行，否则B自行结束"""
NAME = 'keepalive'
def __init__(self):
pass
class ServiceStatusBroadcast(object):
"""服务器定时广播自己的运行状态 pub-channel """
NAME = 'service_status_broadcast'
def __init__(self):
self.service_id = '' #
self.service_type = ''
self.http = '' # 服务器运行的web管理接口地址
class SendOrder(VtOrderReq):
NAME = 'send_order'
def __init__(self):
VtOrderReq.__init__(self)
class Result(object):
def __init__(self):
self.value = [] #订单id列表
def assign(self,data):
if isinstance(data.get('result'),list):
self.value = data.get('result')
return self
class CancelOrder(VtCancelOrderReq):
"""取消订单"""
NAME = 'cancel_order'
def __init__(self):
VtCancelOrderReq.__init__(self)
self.order_id = ''
class Result(object):
def __init__(self):
self.value = False
def assign(self,data):
if data.get('result'):
self.value = VtOrderData()
self.value.__dict__ = data.get('result')
return self
class CancelAllOrders(object):
"""取消所有订单"""
NAME = 'cancel_all_orders'
class SellOrCoverAllTrades(object):
"""平仓所持有的仓位（平金、平⬅昨）"""
NAME = 'sell_or_cover_all_trades'
# class StopOrderRequest(Vt)
class TradeAdapterResponseData(object):
def __init__(self):
self.account = '' # 期货、股票账户名称
self.product = '' # 期货还是股票 feture/stock
class OnPositionData(VtPositionData,TradeAdapterResponseData):
NAME = 'on_position_data'
def __init__(self):
VtPositionData.__init__(self)
TradeAdapterResponseData.__init__(self)
class OnOrderData(VtOrderData,TradeAdapterResponseData):
NAME = 'on_order_data'
def __init__(self):
VtOrderData.__init__(self)
TradeAdapterResponseData.__init__(self)
class OnTradeData(VtTradeData,TradeAdapterResponseData):
NAME = 'on_trade_data'
def __init__(self):
VtTradeData.__init__(self)
TradeAdapterResponseData.__init__(self)
class OnAccountData(VtAccountData,TradeAdapterResponseData):
NAME = 'on_account_data'
def __init__(self):
VtAccountData.__init__(self)
TradeAdapterResponseData.__init__(self)
class GetOrder(object):
NAME = 'get_order'
def __init__(self):
self.order_id = ''
class Result(object):
def __init__(self):
self.value = None
def assign(self,data):
if data.get('result'):
self.value = VtOrderData()
self.value.__dict__ = data.get('result')
return self
class GetAllWorkingOrders(object):
NAME = 'get_all_working_orders'
def __init__(self):
pass
class Result(object):
def __init__(self):
self.value = []
def assign(self,data):
if isinstance(data.get('result'),list):
for r in data.get('result'):
order = VtOrderData()
order.__dict__ = r
self.value.append(order)
return self
class GetAllOrders(GetAllWorkingOrders):
NAME = 'get_all_orders'
def __init__(self):
GetAllWorkingOrders.__init__(self)
class GetAllTrades(object):
NAME = 'get_all_trades'
def __init__(self):
pass
class Result(object):
def __init__(self):
self.value = []
def assign(self,data):
if isinstance(data.get('result'),list):
for r in data.get('result'):
trade = VtTradeData()
trade.__dict__ = r
self.value.append(trade)
return self
class GetAllPositions(object):
NAME = 'get_all_positions'
def __init__(self):
pass
class Result(object):
def __init__(self):
self.value = []
def assign(self,data):
if isinstance(data.get('result'),list):
for r in data.get('result'):
pos = VtPositionData()
pos.__dict__ = r
self.value.append(pos)
return self
class GetAllAccounts(object):
NAME = 'get_all_accounts'
def __init__(self):
pass
class Result(object):
def __init__(self):
self.value = []
def assign(self,data):
if isinstance(data.get('result'),list):
for r in data.get('result'):
account = VtAccountData()
account.__dict__ = r
self.value.append(account)
return self
class StrategyLogContent(object):
"""
策略日志级别
"""
NAME = 'strategy_log_content'
def __init__(self):
self.strategy_id = ''
self.datetime = ''
self.timestamp = 0
self.service_type = ''
self.service_id = ''
self.text = ''
self.level = ''
@property
def plainText(self):
return 'Time:{}|Strategy:{}|Text:{}'.format(self.timestamp,self.strategy_id,self.text)
| 26.14554 | 94 | 0.588975 | 549 | 5,569 | 5.593807 | 0.234973 | 0.093781 | 0.089547 | 0.053728 | 0.390101 | 0.344188 | 0.276457 | 0.276457 | 0.264409 | 0.264409 | 0 | 0.000515 | 0.302747 | 5,569 | 212 | 95 | 26.268868 | 0.790111 | 0.064105 | 0 | 0.529412 | 0 | 0 | 0.076878 | 0.018879 | 0 | 0 | 0 | 0 | 0 | 1 | 0.20915 | false | 0.039216 | 0.013072 | 0.006536 | 0.562092 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2 |
82213f046561e68f8641178deb1971f238462375 | 293 | py | Python | tests/test_home.py | twyle/flask-api-template | 0ad87b13f5bd715c82526fc76ea41710ea75030c | [
"MIT"
] | null | null | null | tests/test_home.py | twyle/flask-api-template | 0ad87b13f5bd715c82526fc76ea41710ea75030c | [
"MIT"
] | 25 | 2022-03-19T14:09:00.000Z | 2022-03-20T09:12:34.000Z | tests/test_home.py | twyle/flask-api-template | 0ad87b13f5bd715c82526fc76ea41710ea75030c | [
"MIT"
] | null | null | null | import pytest
from api import app
@pytest.fixture
def client():
return app.test_client()
def test_home(client):
resp = client.get('/api')
assert resp.status_code == 200
def test_home_bad_http_method(client):
resp = client.post('/api')
assert resp.status_code == 405
| 15.421053 | 38 | 0.692833 | 43 | 293 | 4.534884 | 0.511628 | 0.071795 | 0.112821 | 0.194872 | 0.235897 | 0 | 0 | 0 | 0 | 0 | 0 | 0.025316 | 0.191126 | 293 | 18 | 39 | 16.277778 | 0.797468 | 0 | 0 | 0 | 0 | 0 | 0.027304 | 0 | 0 | 0 | 0 | 0 | 0.181818 | 1 | 0.272727 | false | 0 | 0.181818 | 0.090909 | 0.545455 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
822d83646b1b060682343567ef96b99aa237310e | 183 | py | Python | percivaltts/__init__.py | gillesdegottex/percival-tts | b0cae5ff4fb58b9bc4964be8da5e5f9566abeec9 | [
"Apache-2.0"
] | 2 | 2018-04-16T12:27:43.000Z | 2019-07-22T18:37:07.000Z | percivaltts/__init__.py | gillesdegottex/percival-tts | b0cae5ff4fb58b9bc4964be8da5e5f9566abeec9 | [
"Apache-2.0"
] | 29 | 2018-02-22T14:23:06.000Z | 2018-04-05T14:07:35.000Z | percivaltts/__init__.py | gillesdegottex/percival | b0cae5ff4fb58b9bc4964be8da5e5f9566abeec9 | [
"Apache-2.0"
] | 1 | 2018-09-05T03:45:08.000Z | 2018-09-05T03:45:08.000Z | # This version number has to be updated for each release
# (../setup.py reads this file to obtain the version number of the packages)
__version__ = '2.0.0'
from percivaltts import *
| 30.5 | 76 | 0.748634 | 30 | 183 | 4.433333 | 0.766667 | 0.195489 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.019868 | 0.174863 | 183 | 5 | 77 | 36.6 | 0.860927 | 0.704918 | 0 | 0 | 0 | 0 | 0.098039 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.5 | 0 | 0.5 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 2 |
8235f8b992e581700bc1a8b67788ef755b04d1fe | 614 | py | Python | Python/oib-validation.py | IMilja/oib-validation | fe98afeafe4dd5aac33db0455553966717d875c6 | [
"MIT"
] | null | null | null | Python/oib-validation.py | IMilja/oib-validation | fe98afeafe4dd5aac33db0455553966717d875c6 | [
"MIT"
] | null | null | null | Python/oib-validation.py | IMilja/oib-validation | fe98afeafe4dd5aac33db0455553966717d875c6 | [
"MIT"
] | null | null | null | class oib (object):
def CheckOIB(self,oib=""):
if (len(oib) != 11):
return False
if not oib.isdigit():
return False
a = 10
for i in range(0,10):
a = a + int(oib[i:i+1])
a = a % 10
if a == 0:
a = 10
a *= 2
a = a % 11
kontrolni = 11 - a
if kontrolni == 10:
kontrolni = 0
return kontrolni == int(oib[10:11])
if __name__ == "__main__":
o = oib()
print o.CheckOIB("ovdje upisi oib")
| 21.172414 | 44 | 0.379479 | 72 | 614 | 3.125 | 0.416667 | 0.04 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.082508 | 0.506515 | 614 | 28 | 45 | 21.928571 | 0.660066 | 0 | 0 | 0.190476 | 0 | 0 | 0.039249 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0 | null | null | 0.047619 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
8239dc55c37a6189499182dac81a50b85ca14a32 | 2,792 | py | Python | integration_tests/test_hardware_wallet.py | zanglang/chain-main | 9ccea4d7585cba72e708bf516c41715d1d52f9ad | [
"Apache-2.0"
] | 1 | 2021-07-29T14:29:36.000Z | 2021-07-29T14:29:36.000Z | integration_tests/test_hardware_wallet.py | zanglang/chain-main | 9ccea4d7585cba72e708bf516c41715d1d52f9ad | [
"Apache-2.0"
] | null | null | null | integration_tests/test_hardware_wallet.py | zanglang/chain-main | 9ccea4d7585cba72e708bf516c41715d1d52f9ad | [
"Apache-2.0"
] | null | null | null | import time
from pathlib import Path
import pytest
from .utils import cluster_fixture, get_ledger
pytestmark = pytest.mark.ledger
@pytest.fixture(scope="module")
def cluster(worker_index, pytestconfig, tmp_path_factory):
"override cluster fixture for this test module"
ledger = get_ledger()
ledger.start()
try:
yield from cluster_fixture(
Path(__file__).parent / "configs/ledger.yaml",
worker_index,
tmp_path_factory.mktemp("data"),
quiet=pytestconfig.getoption("supervisord-quiet"),
)
finally:
ledger.stop()
def test_ledger_transfer(cluster):
"""
check simple transfer tx success
- send 1cro from hw to reserve
"""
reserve_addr = cluster.address("reserve")
hw_addr = cluster.address("hw")
reserve_balance = cluster.balance(reserve_addr)
hw_balance = cluster.balance(hw_addr)
tx = cluster.transfer_from_ledger("hw", reserve_addr, "1cro")
print("transfer tx", tx["txhash"])
assert tx["logs"] == [
{
"events": [
{
"attributes": [
{"key": "action", "value": "send"},
{"key": "sender", "value": hw_addr},
{"key": "module", "value": "bank"},
],
"type": "message",
},
{
"attributes": [
{"key": "recipient", "value": reserve_addr},
{"key": "sender", "value": hw_addr},
{"key": "amount", "value": "100000000basecro"},
],
"type": "transfer",
},
],
"log": "",
"msg_index": 0,
}
]
assert cluster.balance(hw_addr) == hw_balance - 100000000
assert cluster.balance(reserve_addr) == reserve_balance + 100000000
def test_wallet_name_for_ledger(cluster):
def check_account(name):
cluster.create_account_ledger(name, 0)
address = cluster.address(name)
assert len(address) > 0
cluster.delete_account(name)
time.sleep(1)
cluster.delete_account("hw")
names = [
"normalwallet",
"abc 1",
# there should be a `\` before `&` and `)` or the terminal will
# trade them as one part of command
r"\&a\)bcd*^",
"钱對중ガジÑá",
# a very long name
"this_is_a_very_long_long_long_long_long_long_\
long_long_long_long_long_long_long_long_name",
# a very complex name
"1 abc &abcd*^ 钱對중ガジÑá long_long_long_long_long_\
long_long_long_long_long_long_long_name",
]
for name in names:
print("name: ", name)
check_account(name)
| 29.389474 | 71 | 0.548352 | 293 | 2,792 | 4.976109 | 0.372014 | 0.131687 | 0.18107 | 0.219479 | 0.108368 | 0.108368 | 0.076818 | 0.076818 | 0.076818 | 0.076818 | 0 | 0.018777 | 0.332378 | 2,792 | 94 | 72 | 29.702128 | 0.763412 | 0.087034 | 0 | 0.09589 | 0 | 0 | 0.132582 | 0 | 0 | 0 | 0 | 0 | 0.054795 | 1 | 0.054795 | false | 0 | 0.054795 | 0 | 0.109589 | 0.027397 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
823f28c32d2bd546b4cbff92817ad336d78d019e | 1,537 | py | Python | src/python3_learn_video/os_module.py | HuangHuaBingZiGe/GitHub-Demo | f3710f73b0828ef500343932d46c61d3b1e04ba9 | [
"Apache-2.0"
] | null | null | null | src/python3_learn_video/os_module.py | HuangHuaBingZiGe/GitHub-Demo | f3710f73b0828ef500343932d46c61d3b1e04ba9 | [
"Apache-2.0"
] | null | null | null | src/python3_learn_video/os_module.py | HuangHuaBingZiGe/GitHub-Demo | f3710f73b0828ef500343932d46c61d3b1e04ba9 | [
"Apache-2.0"
] | null | null | null | """
模块是一个包含所有你定义的函数和变量的文件，其后缀名是.py
模块可以被别的程序引入，以使用该模块中的函数等功能
OS：Operation System 操作系统
"""
import os
print('-------------------------------')
print(os.getcwd()) # 获取当前的目录位置
print('-------------------------------')
os.chdir('E:\\') # 改变当前目录位置
print(os.getcwd())
print('-------------------------------')
print(os.listdir('E:\\')) # 打印当前目录下包含的文件和文件夹
print('-------------------------------')
# os.mkdir('E:\\A') # 创建文件夹
# os.mkdir('E:\\A\\B') # 创建已存在的级联文件夹
# os.makedirs('E:\\B\\C') # 创建级联文件夹
# os.makedirs('E:\\B\\A') # 创建级联文件夹
# os.system('cmd') # 打开cmd
# os.system('calc') # 打开计算器
print(os.curdir) # 当前路径
print(os.listdir(os.curdir)) # 查看当前路径下的文件和文件夹
print('-------------------------------')
print(os.path.basename('E:\\oracle\\hosts')) # 去除路径返回文件名
print('-------------------------------')
print(os.path.dirname('E:\\oracle\\hosts')) # 去除文件名返回路径
print('-------------------------------')
print(os.path.join('A', 'B', 'C'))
print(os.path.join(r'C:\\', 'A', 'B', 'C'))
print(os.path.split('E:\\A\\SEXY.AVI'))
print(os.path.split('E:\\A\\B\\C'))
print('-------------------------------')
print(os.path.splitext('E:\\A\\SEXY.AVI')) # 获取后缀
print('-------------------------------')
print(os.path.getatime('E:\\test.txt'))
import time
print(time.gmtime(os.path.getatime('E:\\test.txt')))
print('-------------------------------')
print(time.localtime(os.path.getatime('E:\\test.txt')))
print('-------------------------------')
print(time.localtime(os.path.getmtime('E:\\test.txt')))
print('-------------------------------')
| 26.964912 | 57 | 0.476252 | 173 | 1,537 | 4.231214 | 0.312139 | 0.143443 | 0.120219 | 0.10929 | 0.233607 | 0.233607 | 0.131148 | 0.131148 | 0.131148 | 0.131148 | 0 | 0 | 0.071568 | 1,537 | 56 | 58 | 27.446429 | 0.512964 | 0.221861 | 0 | 0.451613 | 0 | 0 | 0.438837 | 0.318221 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.064516 | 0 | 0.064516 | 0.903226 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 2 |
4132a073c27ca3eda748f275ea77ed4c9d307c94 | 255 | py | Python | djangozmq/tests/simpletasks.py | lahim/django-zmq | 086d030e87e774b8da8f21eb96a2919d272e88f2 | [
"MIT"
] | null | null | null | djangozmq/tests/simpletasks.py | lahim/django-zmq | 086d030e87e774b8da8f21eb96a2919d272e88f2 | [
"MIT"
] | 9 | 2019-09-10T18:24:55.000Z | 2022-02-10T13:24:27.000Z | djangozmq/tests/simpletasks.py | lahim/django-zmq | 086d030e87e774b8da8f21eb96a2919d272e88f2 | [
"MIT"
] | 1 | 2021-11-15T21:30:56.000Z | 2021-11-15T21:30:56.000Z | def foo_task():
print('Foo task is running...')
print('Foo task completed.')
return True
def sum_task(arg_1: int, arg_2: int):
print('Sum task is running...')
result = arg_1 + arg_2
print('Sum task completed.')
return result
| 21.25 | 37 | 0.627451 | 39 | 255 | 3.948718 | 0.384615 | 0.136364 | 0.155844 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.020513 | 0.235294 | 255 | 11 | 38 | 23.181818 | 0.769231 | 0 | 0 | 0 | 0 | 0 | 0.321569 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.222222 | false | 0 | 0 | 0 | 0.444444 | 0.444444 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 2 |
41332490a94698437b4a87e9d6fc01c6cbc8a637 | 659 | py | Python | tests/base_tests/expression_tests/test_evaluate.py | lycantropos/symba | 279bf86311d50fde55d17c843391f9f83ea31ddf | [
"MIT"
] | 2 | 2021-03-15T12:23:15.000Z | 2022-03-26T21:20:54.000Z | tests/base_tests/expression_tests/test_evaluate.py | lycantropos/symba | 279bf86311d50fde55d17c843391f9f83ea31ddf | [
"MIT"
] | null | null | null | tests/base_tests/expression_tests/test_evaluate.py | lycantropos/symba | 279bf86311d50fde55d17c843391f9f83ea31ddf | [
"MIT"
] | null | null | null | from numbers import Real
from hypothesis import given
from symba.base import Expression
from . import strategies
@given(strategies.definite_expressions)
def test_basic(expression: Expression) -> None:
result = expression.evaluate()
assert isinstance(result, Real)
@given(strategies.definite_expressions)
def test_commutation_with_abs(expression: Expression) -> None:
result = expression.evaluate()
assert abs(result) == abs(expression).evaluate()
@given(strategies.definite_expressions)
def test_commutation_with_neg(expression: Expression) -> None:
result = expression.evaluate()
assert -result == (-expression).evaluate()
| 23.535714 | 62 | 0.766313 | 73 | 659 | 6.780822 | 0.328767 | 0.181818 | 0.193939 | 0.206061 | 0.636364 | 0.636364 | 0.553535 | 0.226263 | 0 | 0 | 0 | 0 | 0.135053 | 659 | 27 | 63 | 24.407407 | 0.868421 | 0 | 0 | 0.375 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.1875 | 1 | 0.1875 | false | 0 | 0.25 | 0 | 0.4375 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
4148e8e876b1d470c83ea099fc60e41be16774ad | 80 | py | Python | examples/old_examples/basic_example.py | ahuang11/ahh | 59f124c3aa04cde58db0ec2e81025eb63a92404e | [
"MIT"
] | 6 | 2016-09-01T03:43:20.000Z | 2018-02-15T00:49:29.000Z | examples/old_examples/basic_example.py | ahuang11/ahh | 59f124c3aa04cde58db0ec2e81025eb63a92404e | [
"MIT"
] | 33 | 2017-10-21T19:03:52.000Z | 2020-10-19T15:05:50.000Z | examples/old_examples/basic_example.py | ahuang11/ahh | 59f124c3aa04cde58db0ec2e81025eb63a92404e | [
"MIT"
] | 2 | 2016-10-14T18:45:39.000Z | 2020-02-02T12:23:20.000Z | from ahh import vis
x = [1, 2, 3, 4]
y = [5, 6, 7, 8]
vis.plot_line(x, y)
| 13.333333 | 20 | 0.5 | 19 | 80 | 2.052632 | 0.842105 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.142857 | 0.3 | 80 | 5 | 21 | 16 | 0.553571 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.25 | 0 | 0.25 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
4148fdc5d64445f429e56e204a83fc4b549ab167 | 6,956 | py | Python | tests/test_models.py | chgans/django-google-dork | c8735f2d2a9740844001cf4430263ea79827102f | [
"BSD-2-Clause"
] | 1 | 2019-07-21T02:32:03.000Z | 2019-07-21T02:32:03.000Z | tests/test_models.py | chgans/django-google-dork | c8735f2d2a9740844001cf4430263ea79827102f | [
"BSD-2-Clause"
] | null | null | null | tests/test_models.py | chgans/django-google-dork | c8735f2d2a9740844001cf4430263ea79827102f | [
"BSD-2-Clause"
] | null | null | null | from django.test import TestCase
from django.db import IntegrityError
from django.core.exceptions import ValidationError
from django_google_dork.models import SearchEngine, Campaign, Dork, Run, Result
class TestCampaign(TestCase):
def setUp(self):
pass
def test_name_not_empty(self):
with self.assertRaises(ValidationError):
c = Campaign.objects.create(name="")
c.full_clean()
def test_name_is_stripped(self):
c = Campaign.objects.create(name=" test ")
c.full_clean()
self.assertEqual(c.name, "test")
def test_name_is_long_enough(self):
with self.assertRaises(ValidationError):
c = Campaign.objects.create(name="t"*3)
c.full_clean()
def test_name_is_short_enough(self):
with self.assertRaises(ValidationError):
c = Campaign.objects.create(name="t"*33)
c.full_clean()
def test_name_is_unique(self):
with self.assertRaises(IntegrityError):
Campaign.objects.create(name="test")
Campaign.objects.create(name="test")
def test_run_set(self):
e = SearchEngine.objects.create(hostname="google.fr")
c = Campaign.objects.create(name="campaign")
d = Dork.objects.create(campaign=c, query="query")
n = 3
for i in range(n):
r = Run.objects.create(dork=d, engine=e)
self.assertEqual(c.run_set.count(), n)
self.assertEqual(c.run_set.last(), r)
self.assertEqual(c.run_set.last(), d.run_set.last())
def test_result_set(self):
e = SearchEngine.objects.create(hostname="google.fr")
c = Campaign.objects.create(name="campaign")
d = Dork.objects.create(campaign=c, query="query")
r = Run.objects.create(dork=d, engine=e)
n = 3
for i in range(n):
s = Result.objects.create(title="title%d" % (i),
summary="summary",
url="http://some.where/path")
r.result_set.add(s)
self.assertEqual(c.result_set.count(), n)
self.assertEqual(c.result_set.last(), s)
self.assertEqual(c.result_set.last(), r.result_set.last())
class TestDork(TestCase):
def setUp(self):
pass
def test_campaign_not_null(self):
with self.assertRaises(IntegrityError):
d = Dork.objects.create()
d.full_clean()
def test_query_not_null(self):
c = Campaign.objects.create(name="c")
with self.assertRaises(IntegrityError):
d = Dork.objects.create(campaign=c, query=None)
def test_query_not_empty(self):
c = Campaign.objects.create(name="c")
with self.assertRaises(ValidationError):
d = Dork.objects.create(campaign=c, query="")
d.full_clean()
def test_query_is_stripped(self):
c = Campaign.objects.create(name="c")
d = Dork.objects.create(campaign=c, query=" test ")
d.full_clean()
self.assertEqual(d.query, "test")
def test_query_is_long_enough(self):
c=Campaign.objects.create(name="c")
with self.assertRaises(ValidationError):
d = Dork.objects.create(campaign=c, query="t"*0)
d.full_clean()
def test_query_is_short_enough(self):
c = Campaign.objects.create(name="c")
with self.assertRaises(ValidationError):
d=Dork.objects.create(campaign=c, query="t"*257)
d.full_clean()
def test_campaign_and_query_00(self):
c0 = Campaign.objects.create(name="c0")
c1 = Campaign.objects.create(name="c1")
Dork.objects.create(campaign=c0, query="test0")
Dork.objects.create(campaign=c1, query="test1")
def test_campaign_and_query_01(self):
c0 = Campaign.objects.create(name="c0")
c1 = Campaign.objects.create(name="c1")
Dork.objects.create(campaign=c0, query="test")
Dork.objects.create(campaign=c1, query="test")
def test_campaign_and_query_10(self):
c = Campaign.objects.create(name="c")
Dork.objects.create(campaign=c, query="test0")
Dork.objects.create(campaign=c, query="test1")
def test_campaign_and_query_11(self):
c = Campaign.objects.create(name="c")
Dork.objects.create(campaign=c, query="test")
with self.assertRaises(IntegrityError):
Dork.objects.create(campaign=c, query="test")
def test_result_set(self):
e = SearchEngine.objects.create(hostname="google.fr")
c = Campaign.objects.create(name="campaign")
d = Dork.objects.create(campaign=c, query="query")
r = Run.objects.create(dork=d, engine=e)
for i in range(3):
s = Result.objects.create(title="title%d" % i,
summary="summary",
url="http://some.where/path")
r.result_set.add(s)
self.assertEqual(d.result_set.count(), 3)
self.assertEqual(d.result_set.last(), s)
self.assertEqual(d.result_set.last(), r.result_set.last())
class TestRun(TestCase):
def setUp(self):
pass
def test_create_dork_not_empty(self):
e = SearchEngine.objects.create(hostname="google.fr")
with self.assertRaises(IntegrityError):
Run.objects.create(engine=e)
def test_create_engine_not_empty(self):
c = Campaign.objects.create(name="campaign")
d = Dork.objects.create(campaign=c, query="query")
with self.assertRaises(IntegrityError):
Run.objects.create(dork=d)
def test_create_wo_results(self):
e = SearchEngine.objects.create(hostname="google.fr")
c = Campaign.objects.create(name="campaign")
d = Dork.objects.create(campaign=c, query="query")
r = Run.objects.create(dork=d, engine=e)
# result_set doen't contains 2 identical result
# This is actually enforced by Django itself!
def test_result_uniqness(self):
e = SearchEngine.objects.create(hostname="google.fr")
c = Campaign.objects.create(name="campaign")
d = Dork.objects.create(campaign=c, query="query")
r = Run.objects.create(dork=d, engine=e)
s = Result.objects.create(title="title",
summary="summary",
url="http://some.where/path")
r.result_set.add(s)
r.result_set.add(s)
self.assertEqual(r.result_set.count(), 1)
class TestResult(TestCase):
def setUp(self):
pass
def create_result(self):
r = Result.objects.create(title="title",
summary="summary",
url="http://some.where/path")
return r
def test_uniqness(self):
r = self.create_result()
with self.assertRaises(IntegrityError):
self.create_result()
| 36.418848 | 79 | 0.609977 | 866 | 6,956 | 4.778291 | 0.112009 | 0.188497 | 0.116723 | 0.138956 | 0.813678 | 0.769212 | 0.690913 | 0.565491 | 0.487434 | 0.487434 | 0 | 0.007204 | 0.261645 | 6,956 | 190 | 80 | 36.610526 | 0.798481 | 0.012795 | 0 | 0.558442 | 0 | 0 | 0.051719 | 0 | 0 | 0 | 0 | 0 | 0.162338 | 1 | 0.181818 | false | 0.025974 | 0.025974 | 0 | 0.24026 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
4154d8d60ee9fcb304dfd74b89b4915e68520767 | 297 | py | Python | Service_3/application/routes.py | emmanuelagyapong/SFIA-2 | 26b56da04fce778f9a1c47187bcda0de316bc5e6 | [
"Unlicense"
] | null | null | null | Service_3/application/routes.py | emmanuelagyapong/SFIA-2 | 26b56da04fce778f9a1c47187bcda0de316bc5e6 | [
"Unlicense"
] | null | null | null | Service_3/application/routes.py | emmanuelagyapong/SFIA-2 | 26b56da04fce778f9a1c47187bcda0de316bc5e6 | [
"Unlicense"
] | 1 | 2020-07-21T13:59:13.000Z | 2020-07-21T13:59:13.000Z | from application import app
from flask import render_template, request
import random
@app.route('/buildingfullname2', methods=['GET'])
def secondname():
list2=['benson', 'hesketh', 'ahmed', 'jennifer', 'oskar']
response2=list2[random.randint(0, len(list2)-1)]
return response2
| 22.846154 | 61 | 0.703704 | 35 | 297 | 5.942857 | 0.771429 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.031621 | 0.148148 | 297 | 13 | 62 | 22.846154 | 0.790514 | 0 | 0 | 0 | 0 | 0 | 0.174497 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.125 | false | 0 | 0.375 | 0 | 0.625 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 2 |
417bc34f67e5a524598bfd1540a511f3121fda52 | 8,733 | py | Python | Schedule/accounts/serializers.py | f0rdream/party-time | 3b596043627383859042a6e70167e4304bab9a92 | [
"MIT"
] | null | null | null | Schedule/accounts/serializers.py | f0rdream/party-time | 3b596043627383859042a6e70167e4304bab9a92 | [
"MIT"
] | null | null | null | Schedule/accounts/serializers.py | f0rdream/party-time | 3b596043627383859042a6e70167e4304bab9a92 | [
"MIT"
] | null | null | null | from django.contrib.contenttypes.models import ContentType
from django.urls import reverse_lazy
from rest_framework.fields import BooleanField, NullBooleanField
from rest_framework_jwt.serializers import JSONWebTokenSerializer
from tasks.models import Task
from .models import UserProfile,upload_location
from django.contrib.auth.models import User, Permission
from rest_framework.serializers import (
CharField,
EmailField,
ImageField,
HyperlinkedIdentityField,
ModelSerializer,
SerializerMethodField,
ValidationError
)
class UserProfileDetailSerializer(ModelSerializer):
user = SerializerMethodField()
email = SerializerMethodField()
picture = ImageField(use_url=True)
class Meta:
model = UserProfile
fields = [
'user',
'real_name',
'description',
'email',
'user_stu_id',
'school',
'picture',
'phone_number',
]
def get_user(self, obj):
return str(obj.user.username)
def get_email(self, obj):
return str(obj.user.email)
def get_picture(self, obj):
try:
picture = obj.picture.url
except:
picture = None
return picture
class UserUpdateSerializer(ModelSerializer):
"""
Serializer to update user profile
"""
user = SerializerMethodField()
email = SerializerMethodField()
picture = ImageField(use_url=True, allow_empty_file=True, allow_null=True)
class Meta:
model = UserProfile
fields = [
'user',
'real_name',
'email',
'description',
'user_stu_id',
'phone_number',
'school',
'picture',
]
read_only_fields = [
'user',
'email',
]
def get_user(self, obj):
return str(obj.user.username)
def get_email(self, obj):
return str(obj.user.email)
def get_picture(self, obj):
try:
picture = obj.picture.url
except:
picture = None
return picture
def update(self, instance, validated_data):
if validated_data['picture'] is None and instance.picture is not None:
validated_data['picture'] = instance.picture
return super(UserUpdateSerializer, self).update(instance, validated_data)
class UserProfileCreateSerializer(ModelSerializer):
user = SerializerMethodField()
# email = SerializerMethodField()
class Meta:
model = UserProfile
fields = [
'user',
# 'email',
'user_stu_id',
'real_name',
'description',
'phone_number',
'school',
]
def get_user(self, obj):
return str(obj.user.username)
class UserCreateSerializer(ModelSerializer):
email = EmailField(label='Email Address')
password = CharField(label='Password',
write_only=True,
style={'input_type': 'password'})
password_confirm = CharField(label='Confirm Password',
write_only=True,
style={'input_type': 'password'})
user_profile = UserProfileCreateSerializer(write_only=True)
profile = UserProfileCreateSerializer(read_only=True)
class Meta:
model = User
fields = [
'username',
'email',
'password',
'password_confirm',
'user_profile',
'profile',
]
extra_kwargs = {
"password": {"write_only": True}
}
def validate(self, attrs):
print attrs
del attrs['password_confirm']
return attrs
# def validate_password_confirm(self, value):
# data = self.get_initial()
# password = data.get('password')
# password_confirm = data.get('password_confirm')
# if password != password_confirm:
# raise ValidationError("The password is not confirmed")
# return value
def validate_email(self, value):
data = self.get_initial()
email = data.get('email')
user_queryset = User.objects.filter(email=email)
if user_queryset.exists():
raise ValidationError("This email has been registered.")
return value
def validate_username(self, value):
data = self.get_initial()
username = data.get('username')
if len(username) < 9:
raise ValidationError("The username must be more than 9 digits.")
user_qs = User.objects.filter(username=username)
if user_qs.exists():
raise ValidationError("The username has been registered.")
return value
def create_user_profile(self,user_obj , profile_data):
real_name = profile_data['real_name']
student_id = profile_data['user_stu_id']
school = profile_data['school']
user_profile = UserProfile(user=user_obj,
real_name=real_name,
user_stu_id=student_id,
school=school)
user_profile.save()
def create(self, validated_data):
# print validated_data
username = validated_data['username']
email = validated_data['email']
password = validated_data['password']
user_obj = User(username=username,
email=email)
user_obj.set_password(password)
user_obj.save()
# user_obj.is_active = False
# content_type = ContentType.objects.get_for_model(Task)
# permission_to_add = Permission.objects.get(codename="add_task",
# content_type=content_type)
# permission_to_change = Permission.objects.get(codename="change_task",
# content_type=content_type)
# permission_to_delete = Permission.objects.get(codename="delete_task",
# content_type=content_type)
# user_obj.user_permissions.add(permission_to_add, permission_to_change, permission_to_delete)
print "succeed create a user"
self.create_user_profile(user_obj, validated_data['user_profile'])
return user_obj
class UserSearchSerializer(ModelSerializer):
"""
search for user registered
"""
picture = SerializerMethodField(read_only=True)
class Meta:
model = User
fields = [
'id',
'username',
'picture',
]
def get_picture(self, obj):
username = obj.username
try:
user = User.objects.get(username=username)
user_profile = UserProfile.objects.get(user=user)
try:
picture = user_profile.picture.url
except:
picture = None
return picture
except User.DoesNotExist:
return None
except UserProfile.DoesNotExist:
return None
class UserLoginSerializer(ModelSerializer):
token = CharField(read_only=True, allow_blank=True)
username = CharField()
remembered = BooleanField(write_only=True, required=False)
password = CharField(style={'input_type': 'password'})
picture = SerializerMethodField(read_only=True)
# password = PasswordField()
class Meta:
model = User
fields = [
'username',
'password',
'token',
'remembered',
'picture',
]
extra_kwargs = {
"password": {"write_only": True}
}
def validate(self, data):
return data
def get_picture(self, obj):
username = obj['username']
try:
user = User.objects.get(username=username)
user_profile = UserProfile.objects.get(user=user)
try:
picture = user_profile.picture.url
except:
picture = None
return picture
except User.DoesNotExist:
return None
except UserProfile.DoesNotExist:
return None
class LoadUserPictureSerializer(ModelSerializer):
picture = SerializerMethodField()
class Meta:
model = UserProfile
fields = [
'picture'
]
def get_picture(self, obj):
return obj.picture.url
class UserAddGroupSerializer(ModelSerializer):
"""
Serializer to add and remove group.
"""
class Meta:
model = User
fields = [
'groups',
]
| 29.11 | 102 | 0.578152 | 815 | 8,733 | 6.022086 | 0.177914 | 0.026895 | 0.02282 | 0.0163 | 0.393236 | 0.356968 | 0.29075 | 0.275265 | 0.243073 | 0.173798 | 0 | 0.000344 | 0.334249 | 8,733 | 299 | 103 | 29.207358 | 0.843825 | 0.110157 | 0 | 0.551111 | 0 | 0 | 0.08914 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0.057778 | 0.035556 | null | null | 0.008889 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 |
4189ebce3b587d5d121a8faac4d08a070bfc045c | 422 | py | Python | python_parser_api/src/routes.py | FaceandControl/genshin-parser | b18700ad9f6561d763a128df77d3b977fd23fd37 | [
"MIT"
] | null | null | null | python_parser_api/src/routes.py | FaceandControl/genshin-parser | b18700ad9f6561d763a128df77d3b977fd23fd37 | [
"MIT"
] | null | null | null | python_parser_api/src/routes.py | FaceandControl/genshin-parser | b18700ad9f6561d763a128df77d3b977fd23fd37 | [
"MIT"
] | null | null | null | from src import api
from src.resources.main import Main
from src.resources.character import Сharacter
from src.resources.characters import Сharacters
#
# Declarations of app routes in type of rest web-architecture
#
# routes
api.add_resource(Main, '/', strict_slashes=False)
api.add_resource(Сharacter, '/<ln>/character/<name>', strict_slashes=False)
api.add_resource(Сharacters, '/<ln>/characters', strict_slashes=False) | 35.166667 | 75 | 0.796209 | 59 | 422 | 5.59322 | 0.440678 | 0.084848 | 0.145455 | 0.127273 | 0.193939 | 0.193939 | 0 | 0 | 0 | 0 | 0 | 0 | 0.092417 | 422 | 12 | 76 | 35.166667 | 0.861619 | 0.156398 | 0 | 0 | 0 | 0 | 0.110795 | 0.0625 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.571429 | 0 | 0.571429 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 2 |
41b1bdae0490a6de481f61f0363f93cb35c1aea9 | 1,864 | py | Python | utils.py | EliorBenYosef/data-science | 117e5254f63e482c02aff394780bbdc205d492a3 | [
"MIT"
] | null | null | null | utils.py | EliorBenYosef/data-science | 117e5254f63e482c02aff394780bbdc205d492a3 | [
"MIT"
] | null | null | null | utils.py | EliorBenYosef/data-science | 117e5254f63e482c02aff394780bbdc205d492a3 | [
"MIT"
] | null | null | null | import numpy as np
import matplotlib.pyplot as plt
def plot_hist_sum(data, r_labels, ylabel, xlabel, title, x_tick_labels=None, adjacent_bars=True):
"""
plots Histogram of sum
plots multiple bars
"""
n_rows = len(r_labels)
total_bars_width = 0.8
bar_width = total_bars_width / n_rows
# bins = np.linspace(1, d, d)
bins = np.arange(data.shape[1]) + 1 # d = data.shape[1]
fig, ax = plt.subplots(figsize=(10, 6))
for i in range(n_rows):
if adjacent_bars:
ax.bar(x=bins + (i * bar_width) - total_bars_width / 2 + bar_width / 2,
height=data[i], width=bar_width, align='center', label=r_labels[i])
else: # overlapping\superimposed bars
ax.bar(x=bins, height=data[i], alpha=0.75, width=total_bars_width, align='center', label=r_labels[i])
ax.legend(loc='best')
ax.set_ylabel(ylabel)
ax.set_xlabel(xlabel)
ax.set_xticks(bins)
if x_tick_labels is not None:
ax.set_xticklabels(x_tick_labels)
ax.set_title(title)
def plot_hist_count(data, r_labels, ylabel, xlabel, title, x_tick_labels=None, adjacent_bars=True):
"""
plots Histogram of count
"""
n_rows = len(r_labels)
total_bars_width = 0.8
bar_width = total_bars_width / n_rows
# bins = np.linspace(1, d, d)
bins = np.arange(data.shape[1]) + 1 # d = data.shape[1]
fig, ax = plt.subplots(figsize=(10, 6))
if adjacent_bars:
ax.hist(x=data, bins=bins, label=r_labels)
else: # overlapping\superimposed bars
for i in range(n_rows): # alpha=0.5
ax.hist(x=data[i], bins=bins, alpha=0.5, label=r_labels[i])
ax.legend(loc='best')
ax.set_ylabel(ylabel)
ax.set_xlabel(xlabel)
ax.set_xticks(bins)
if x_tick_labels is not None:
ax.set_xticklabels(x_tick_labels)
ax.set_title(title)
| 31.59322 | 113 | 0.642167 | 300 | 1,864 | 3.786667 | 0.24 | 0.044014 | 0.058099 | 0.066901 | 0.729754 | 0.685739 | 0.65757 | 0.617958 | 0.617958 | 0.617958 | 0 | 0.018815 | 0.23015 | 1,864 | 58 | 114 | 32.137931 | 0.772822 | 0.123391 | 0 | 0.769231 | 0 | 0 | 0.012555 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.051282 | false | 0 | 0.051282 | 0 | 0.102564 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
41c0e0c72524f09f1f567700371524de838cae79 | 393 | py | Python | backend/users/admin.py | madarconsulting/django-twitter-spark | aac2cbf1b697a3eec3e7a20f0dc0c30ebfeab6c8 | [
"MIT"
] | 8 | 2019-07-19T13:50:59.000Z | 2021-09-01T03:39:23.000Z | backend/users/admin.py | madarconsulting/django-twitter-spark | aac2cbf1b697a3eec3e7a20f0dc0c30ebfeab6c8 | [
"MIT"
] | 22 | 2019-11-11T15:56:04.000Z | 2022-03-24T03:29:57.000Z | backend/users/admin.py | madarconsulting/django-twitter-spark | aac2cbf1b697a3eec3e7a20f0dc0c30ebfeab6c8 | [
"MIT"
] | 3 | 2019-12-14T04:59:11.000Z | 2021-09-01T03:39:28.000Z | from django.contrib import admin
# Register your models here.
from api.models import (User,Dictionary,CustomDictionary,Topic,Search,
WordRoot,SocialNetworkAccounts)
admin.site.register(User)
admin.site.register(Dictionary)
admin.site.register(CustomDictionary)
admin.site.register(Topic)
admin.site.register(Search)
admin.site.register(WordRoot)
admin.site.register(SocialNetworkAccounts)
| 26.2 | 70 | 0.834606 | 48 | 393 | 6.833333 | 0.375 | 0.192073 | 0.362805 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.063613 | 393 | 14 | 71 | 28.071429 | 0.891304 | 0.066158 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.2 | 0 | 0.2 | 0 | 0 | 0 | 0 | null | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
41c14081a7c6761500ead5314ac65338343a04f0 | 728 | py | Python | notes/code/twitter/trump_tweets.py | adamreevesman/msds692 | ad1317c0e688f1a7c135d6933e9942068724b761 | [
"MIT"
] | null | null | null | notes/code/twitter/trump_tweets.py | adamreevesman/msds692 | ad1317c0e688f1a7c135d6933e9942068724b761 | [
"MIT"
] | null | null | null | notes/code/twitter/trump_tweets.py | adamreevesman/msds692 | ad1317c0e688f1a7c135d6933e9942068724b761 | [
"MIT"
] | null | null | null | import tweepy
def loadkeys(filename):
""""
load parrt's keys/tokens from CSV file with form
consumer_key, consumer_secret, access_token, access_token_secret
"""
with open(filename) as f:
items = f.readline().strip().split(', ')
return items
consumer_key, consumer_secret, \
access_token, access_token_secret \
= loadkeys("/Users/parrt/Dropbox/licenses/twitter.csv")
auth = tweepy.OAuthHandler(consumer_key, consumer_secret)
auth.set_access_token(access_token, access_token_secret)
api = tweepy.API(auth)
user = api.get_user('realDonaldTrump')
print "followers", user.followers_count
for status in tweepy.Cursor(api.user_timeline, id='realDonaldTrump').items(100):
print status | 26.962963 | 80 | 0.737637 | 96 | 728 | 5.385417 | 0.510417 | 0.148936 | 0.131528 | 0.170213 | 0.259188 | 0.205029 | 0.205029 | 0.205029 | 0.205029 | 0 | 0 | 0.004847 | 0.149725 | 728 | 27 | 81 | 26.962963 | 0.830372 | 0 | 0 | 0 | 0 | 0 | 0.137815 | 0.068908 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0.066667 | null | null | 0.133333 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
41c63abb535ee35ebba61ee250c2ecab6948e7ba | 3,539 | py | Python | hard-gists/2787060/snippet.py | jjhenkel/dockerizeme | eaa4fe5366f6b9adf74399eab01c712cacaeb279 | [
"Apache-2.0"
] | 21 | 2019-07-08T08:26:45.000Z | 2022-01-24T23:53:25.000Z | hard-gists/2787060/snippet.py | jjhenkel/dockerizeme | eaa4fe5366f6b9adf74399eab01c712cacaeb279 | [
"Apache-2.0"
] | 5 | 2019-06-15T14:47:47.000Z | 2022-02-26T05:02:56.000Z | hard-gists/2787060/snippet.py | jjhenkel/dockerizeme | eaa4fe5366f6b9adf74399eab01c712cacaeb279 | [
"Apache-2.0"
] | 17 | 2019-05-16T03:50:34.000Z | 2021-01-14T14:35:12.000Z | # -*- coding:UTF8 -*-
#1.概念：
# 正则表达式（或 RE）是一种小型的、高度专业化的编程语言，
# （在Python中）它内嵌在Python中，并通过 re 模块实现。使用这个小型语言，
# 你可以为想要匹配的相应字符串集指定规则；该字符串集可能包含英文语句、email
# 地址、TeX命令或任何你想搞定的东西。然后你可以问诸如“这个字符串匹配
# 该模式吗？”或“在这个字符串中是否有部分匹配该模式呢？”。你也可以使用 RE
# 以各种方式来修改或分割字符串。
#
# 正则表达式语言相对小型和受限（功能有限），因此并非所有字符串处理都能用
# 正则表达式完成。当然也有些任务可以用正则表达式完成，不过最终表达式会变
# 得异常复杂。碰到这些情形时，编写 Python 代码进行处理可能反而更好；尽管
# Python 代码比一个精巧的正则表达式要慢些，但它更易理解。
#
#2.在正则表达式中， 如下的字符是具有特殊含义的
# . (所有字符) ^ $ *(0-N次) +(1-N次) ? (0-1次) { } [ ] \ | ( )
# 1)."[" 和 "]"。它们常用来指定一个字符类别，所谓字符类别就是你想匹配的一个字符集
# 2).其它地方的"^"只会简单匹配 "^"字符本身。例[^5] 将匹配除 "5" 之外的任意字符。
# 3).反斜杠后面可以加不同的字符以表示不同特殊意义。它也可以用于取消所有的元字符
#
#3.RE 函数用法:
# findall(rule , target [,flag] ) 在目标字符串中查找符合规则的字符串。
# match() 决定 RE 是否在字符串刚开始的位置匹配
# search() 扫描字符串，找到这个 RE 匹配的位置
# findall() 找到 RE 匹配的所有子串，并把它们作为一个列表返回
# finditer() 找到 RE 匹配的所有子串，并把它们作为一个迭代器返回
# group() 返回被 RE 匹配的字符串
# start() 返回匹配开始的位置
# end() 返回匹配结束的位置
# span() 返回一个元组包含匹配 (开始,结束) 的位置
# compile( rule [,flag] )将正则规则编译成一个Pattern对象，以供接下来使用第一个参数
#
# 是规则式，第二个参数是规则选项。(使用compile加速)
#
#4 : 含义:
# 预定义转义字符集： “\d” “\w” “\s” 等等，它们是以字符’\’开头，后面接一个特定
#
#字符的形式,用来指示一个预定义好的含义
#
# ‘^’ 和’$’ 匹配字符串开头和结尾
# ‘.’ 匹配所有字符 除\n以外
# ‘\d’ 匹配数字
# ‘\D’ 匹配非数字
# ‘\w’ 匹配字母和数字
# ‘\W’ 匹配非英文字母和数字
# ‘\s’ 匹配间隔符
# ‘\S’ 匹配非间隔符
# ‘\A’ 匹配字符串开头
# ‘\Z’ 匹配字符串结尾
# ‘\b’ 只用以匹配单词的词首和词尾。单词被定义为一个字母数字序列，因此词尾就
#
# 是用空白符或非字母数字符来标示的。(退格)
# ‘\B’，它正好同 \b 相反，只在当前位置不在单词边界时匹配。
#5.前向界定与后向界定:
# ‘(?<=…)’ 前向界定:括号中’…’代表你希望匹配的字符串的前面应该出现的字符串。
# ‘(?=…)’后向界定 :括号中的’…’代表你希望匹配的字符串后面应该出现的字符串
# ‘(?<!..)’前向非界定 :只有当你希望的字符串前面不是’…’的内容时才匹配
# ‘(?!...)’后向非界定 :只有当你希望的字符串后面不跟着’…’内容时才匹配。
#6.组的基本知识:
# ‘(‘’)’ 无命名组 [a-z]+(\d+)[a-z]+
# ‘(?P<name>…)’ 命名组 (?P<g1>[a-z]+)\d+(?P=g1)
# ‘(?P=name)’ 调用已匹配的命名组
# ‘\number’通过序号调用已匹配的组正则式中的每个组都有一个序号，序号是按组
#
#从左到右，从1开始的数字，你可以通过下面的形式来调用已匹配的组
# ( r"(\d+)([a-z]+)(\d+)(\2)(\1)" )
import sys
reload(sys)
sys.setdefaultencoding('utf-8')
import rhinoscriptsyntax as rs
# 正则表达式
import re
str1 = "abc \\ 123 456"
print re.findall("\\\\",str1) # 不用r和用r的区
print re.findall(r"\d\Z",str1) # 用"r"来定义规则字符串
p = re.compile('(a)b')
m = p.match('ab')
print m.group()
s = "aaa1 22 gg 333 ccc 4444 pppp 55555 666"
print re.findall(r"\b\d{3}\b",s)
print re.findall(r"\b\d{2,4}\b",s)
s2 = "aaa111aaa , bbb222 , 333ccc"
print re.findall( r"(?<=[a-z]+)\d+(?=[a-z]+)",s2 )
print re.findall( r"\d+(?=[a-z]+)",s2 )
## 目标 前面是a-z 1-多次、中间数字1-9 1-多次
print re.findall(r"\d+(?!\w+)",s2)
#无命名组
print re.findall(r"[a-z]+(\d+)[a-z]+",s2) # 只返回()里面的
s3 = 'aaa111aaa,bbb222,333ccc,444ddd444,555eee666,fff777ggg,hhh888hhh'
print re.findall(r"([a-z]+)\d+([a-z]+)",s3) #返回括号里面的
#‘(?P<name>…)’ 命名组
print re.findall( r"(?P<g1>[a-z]+)\d+(?P=g1)",s3 ) #找出被中间夹有数字的前后同样的字母
print re.findall(r"([a-z]+)\d+\1",s3)
s4 = "111aaa222aaa111,333bbb444bb33"
print re.findall( r"(\d+)([a-z]+)(\d+)(\2)(\1)", s4 ) #数字、字母、数字、字母、数字相对称
print re.compile(r"(\d+)([a-z]+)(\d+)(\2)(\1)").findall(s4)
#compile( rule [,flag] ) 使用compile加速
s5 = "111,222,aaa,bbb,ccc333,444ddd"
print re.compile(r"\d+\b").findall(s5) # \退格 匹配一个位于开头的数字，没有使用M选项
s6 = "123 456\n789 012\n345 678"
print re.compile(r"^\d+",re.M).findall(s6) # 匹配位于(M/多行)开头的数字
rcm=re.compile(r"\d+$")# 对于’$’来说，没有使用M选项，它将匹配最后一个行尾的数字，即’678’，加上以后，就能匹配三个行尾的数字456 012和678了.
print re.compile(r"\d+$",re.M).findall(s6) #
| 29.991525 | 91 | 0.587737 | 483 | 3,539 | 4.356108 | 0.488613 | 0.053232 | 0.079848 | 0.078422 | 0.147338 | 0.115494 | 0.099335 | 0.057034 | 0.057034 | 0.020913 | 0 | 0.060912 | 0.188189 | 3,539 | 117 | 92 | 30.247863 | 0.66307 | 0.630687 | 0 | 0 | 0 | 0 | 0.372533 | 0.181743 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0.09375 | null | null | 0.53125 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 2 |
41cee06d65e081783f71b53fff425a032527d5df | 1,327 | py | Python | snekcord/objects/user.py | asleep-cult/snekcord | 04302b0c65bad01c00fb047df3040d3234773689 | [
"MIT"
] | 9 | 2021-07-26T00:25:51.000Z | 2022-02-23T16:00:10.000Z | snekcord/objects/user.py | asleep-cult/snekcord | 04302b0c65bad01c00fb047df3040d3234773689 | [
"MIT"
] | 37 | 2021-05-29T16:16:22.000Z | 2022-02-13T13:57:25.000Z | snekcord/objects/user.py | asleep-cult/snekcord | 04302b0c65bad01c00fb047df3040d3234773689 | [
"MIT"
] | 4 | 2021-06-02T16:45:41.000Z | 2022-02-10T14:57:16.000Z | import enum
from .base import BaseObject
from .. import json
__all__ = ('UserFlags', 'PremiumType', 'User')
class UserFlags(enum.IntFlag):
NONE = 0
STAFF = 1 << 0
PARTNER = 1 << 1
HYPESQUAD = 1 << 2
BUG_HUNTER_LEVEL_1 = 1 << 3
HYPESQUAD_ONLINE_HOUSE_1 = 1 << 6
HYPESQUAD_ONLINE_HOUSE_2 = 1 << 7
HYPESQUAD_ONLINE_HOUSE_3 = 1 << 8
PREMIUM_EARLY_SUPPORTER = 1 << 9
TEAM_PSUEDO_USER = 1 << 10
BUG_HUNTER_LEVEL_2 = 1 << 14
VERIFIED_BOT = 1 << 16
VERIFIED_DEVELOPER = 1 << 17
CERTIFIED_MODERATOR = 1 << 18
BOT_HTTP_INTERACTIONS = 1 << 19
class PremiumType(enum.IntEnum):
NONE = 0
NITRO_CLASSIC = 1
NITRO = 2
class User(BaseObject):
name = json.JSONField('username')
discriminator = json.JSONField('discriminator')
avatar = json.JSONField('avatar')
bot = json.JSONField('bot')
system = json.JSONField('system')
mfa_enabled = json.JSONField('mfa_enabled')
banner = json.JSONField('banner')
accent_color = json.JSONField('accent_color')
locale = json.JSONField('locale')
verified = json.JSONField('verified')
email = json.JSONField('email')
flags = json.JSONField('flags', UserFlags)
premium_type = json.JSONField('premium_type', PremiumType)
public_flags = json.JSONField('public_flags', UserFlags)
| 27.645833 | 62 | 0.666918 | 166 | 1,327 | 5.108434 | 0.39759 | 0.214623 | 0.070755 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.041227 | 0.214017 | 1,327 | 47 | 63 | 28.234043 | 0.771812 | 0 | 0 | 0.051282 | 0 | 0 | 0.10324 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.076923 | 0 | 0.974359 | 0 | 0 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2 |
68ba6868d9de9aa129a3f435e14fa74451010d5a | 505 | py | Python | gallery/search_indexes.py | mingyuchoo/myartworks | 9404dad4b9ee0047049a1a0196cb9ac32ce520d7 | [
"MIT"
] | 1 | 2016-08-16T06:34:36.000Z | 2016-08-16T06:34:36.000Z | gallery/search_indexes.py | mingyuchoo/myartworks | 9404dad4b9ee0047049a1a0196cb9ac32ce520d7 | [
"MIT"
] | null | null | null | gallery/search_indexes.py | mingyuchoo/myartworks | 9404dad4b9ee0047049a1a0196cb9ac32ce520d7 | [
"MIT"
] | null | null | null | import datetime
from haystack import indexes
from .models import Portfolio
class PortfolioIndex(indexes.SearchIndex, indexes.Indexable):
text = indexes.CharField(document=True, use_template=True)
writer = indexes.CharField(model_attr='writer')
created_date = indexes.DateTimeField(model_attr='created_date')
def get_model(self):
return Portfolio
def index_queryset(self, using=None):
return self.get_model().objects.filter(created_date__lte=datetime.datetime.now()) | 33.666667 | 89 | 0.764356 | 62 | 505 | 6.048387 | 0.564516 | 0.088 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.140594 | 505 | 15 | 89 | 33.666667 | 0.864055 | 0 | 0 | 0 | 0 | 0 | 0.035573 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.181818 | false | 0 | 0.272727 | 0.181818 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 2 |
68c2804c261cb3395f497ea7356388228acca5b2 | 104 | py | Python | output/models/saxon_data/open/open035_xsd/__init__.py | tefra/xsdata-w3c-tests | b6b6a4ac4e0ab610e4b50d868510a8b7105b1a5f | [
"MIT"
] | 1 | 2021-08-14T17:59:21.000Z | 2021-08-14T17:59:21.000Z | output/models/saxon_data/open/open035_xsd/__init__.py | tefra/xsdata-w3c-tests | b6b6a4ac4e0ab610e4b50d868510a8b7105b1a5f | [
"MIT"
] | 4 | 2020-02-12T21:30:44.000Z | 2020-04-15T20:06:46.000Z | output/models/saxon_data/open/open035_xsd/__init__.py | tefra/xsdata-w3c-tests | b6b6a4ac4e0ab610e4b50d868510a8b7105b1a5f | [
"MIT"
] | null | null | null | from output.models.saxon_data.open.open035_xsd.open035 import BookStore
__all__ = [
"BookStore",
]
| 17.333333 | 71 | 0.759615 | 13 | 104 | 5.615385 | 0.846154 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.066667 | 0.134615 | 104 | 5 | 72 | 20.8 | 0.744444 | 0 | 0 | 0 | 0 | 0 | 0.086538 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.25 | 0 | 0.25 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
68c6f1b34b6e4cfeab1a63860b03607b490cb0e0 | 252 | py | Python | main.py | Gaoyifei1011/AmapProgram | d45a27abf9f508d922f37abc34f00da6d0aab4a0 | [
"MIT"
] | 1 | 2021-05-19T02:48:49.000Z | 2021-05-19T02:48:49.000Z | main.py | Gaoyifei1011/AmapProgram | d45a27abf9f508d922f37abc34f00da6d0aab4a0 | [
"MIT"
] | 1 | 2021-05-18T16:01:56.000Z | 2021-05-20T02:14:52.000Z | main.py | Gaoyifei1011/AmapProgram | d45a27abf9f508d922f37abc34f00da6d0aab4a0 | [
"MIT"
] | 1 | 2021-06-04T06:39:57.000Z | 2021-06-04T06:39:57.000Z | import sys
from PyQt5 import QtWidgets
from LoginMainWindow import LoginMainWindow
if __name__ == '__main__':
app = QtWidgets.QApplication(sys.argv)
loginWindow = LoginMainWindow()
loginWindow.show()
sys.exit(app.exec_())
| 21 | 44 | 0.706349 | 26 | 252 | 6.5 | 0.615385 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.005 | 0.206349 | 252 | 11 | 45 | 22.909091 | 0.84 | 0 | 0 | 0 | 0 | 0 | 0.033195 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.375 | 0 | 0.375 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 2 |
68d3da6cc68cf283b53b3b77966baa6ebf303b7f | 247 | py | Python | HackerRank/Python3/listComprension.py | santoshgawande/DS-Algorithms | eb1de229fd3336d862bd4787295f208a4424d0bb | [
"Apache-2.0"
] | null | null | null | HackerRank/Python3/listComprension.py | santoshgawande/DS-Algorithms | eb1de229fd3336d862bd4787295f208a4424d0bb | [
"Apache-2.0"
] | null | null | null | HackerRank/Python3/listComprension.py | santoshgawande/DS-Algorithms | eb1de229fd3336d862bd4787295f208a4424d0bb | [
"Apache-2.0"
] | null | null | null | if __name__ == '__main__':
x = int(input())
y = int(input())
z = int(input())
n = int(input())
nlist = [[i,j,k] for i in range(0, x+1) for j in range(0, y+1) for k in range(0, z+1) if (i+j+k) > n or (i+j+k)< n]
print(nlist) | 35.285714 | 119 | 0.510121 | 52 | 247 | 2.269231 | 0.384615 | 0.271186 | 0.076271 | 0.067797 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.032967 | 0.263158 | 247 | 7 | 120 | 35.285714 | 0.615385 | 0 | 0 | 0 | 0 | 0 | 0.032258 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.142857 | 0 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
68e5b9e8269ed15f6fe60de3ea6abf29fde863fa | 513 | py | Python | gpio.py | bengoodwyn/waterbot | e51f290c5f2e50a3b01cc20651a7a6b70c43c8b0 | [
"MIT"
] | null | null | null | gpio.py | bengoodwyn/waterbot | e51f290c5f2e50a3b01cc20651a7a6b70c43c8b0 | [
"MIT"
] | null | null | null | gpio.py | bengoodwyn/waterbot | e51f290c5f2e50a3b01cc20651a7a6b70c43c8b0 | [
"MIT"
] | null | null | null | import os
def __run_or_die(cmd):
if 0 != os.system(cmd):
raise Exception("Failed to run {}".format(cmd))
gpio_cmd = os.getenv("GPIO_COMMAND", "gpio")
def mode_out(pin):
cmd = "{} mode {} out".format(gpio_cmd, pin)
__run_or_die(cmd)
def mode_in(pin):
cmd = "{} mode {} in".format(gpio_cmd, pin)
__run_or_die(cmd)
def on(pin):
cmd = "{} write {} 0".format(gpio_cmd, pin)
__run_or_die(cmd)
def off(pin):
cmd = "{} write {} 1".format(gpio_cmd, pin)
__run_or_die(cmd)
| 21.375 | 55 | 0.614035 | 84 | 513 | 3.416667 | 0.309524 | 0.087108 | 0.139373 | 0.191638 | 0.407666 | 0.407666 | 0.407666 | 0.407666 | 0.313589 | 0 | 0 | 0.007389 | 0.208577 | 513 | 23 | 56 | 22.304348 | 0.699507 | 0 | 0 | 0.235294 | 0 | 0 | 0.165692 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.294118 | false | 0 | 0.058824 | 0 | 0.352941 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
ec044b1d51f76e78f5ae0c52f05400e0ebc6634d | 923 | py | Python | Python Assignments/Python Assignment 6/Assignment6_3.py | Suryakant-Kamble/Python | 6c82205f6fdd511e01bf109aaa2e75da53fb1cea | [
"MIT"
] | null | null | null | Python Assignments/Python Assignment 6/Assignment6_3.py | Suryakant-Kamble/Python | 6c82205f6fdd511e01bf109aaa2e75da53fb1cea | [
"MIT"
] | null | null | null | Python Assignments/Python Assignment 6/Assignment6_3.py | Suryakant-Kamble/Python | 6c82205f6fdd511e01bf109aaa2e75da53fb1cea | [
"MIT"
] | null | null | null | class Arithmetic:
def __init__(self):
self.value1 = 0
self.value2 = 0
def Accept(self, no1, no2):
self.value1 = no1
self.value2 = no2
def Addition(self):
result = self.value1 + self.value2
print("Addition is = ", result)
def Subtraction(self):
result = self.value1 - self.value2
print("Subtraction is = ", result)
def Multiplication(self):
result = self.value1 * self.value2
print("Multiplication is = ", result)
def Division(self):
result = self.value1 / self.value2
print("Division is = ", result)
def main():
a = int(input("Enter value1 : "))
b = int(input("Enter value2 = "))
obj = Arithmetic()
obj.Accept(a, b)
obj.Addition()
obj.Subtraction()
obj.Multiplication()
obj.Division()
if __name__ == '__main__':
main()
| 23.075 | 46 | 0.551463 | 100 | 923 | 4.97 | 0.27 | 0.120724 | 0.112676 | 0.160966 | 0.28169 | 0.28169 | 0.28169 | 0 | 0 | 0 | 0 | 0.032103 | 0.325027 | 923 | 39 | 47 | 23.666667 | 0.76565 | 0 | 0 | 0 | 0 | 0 | 0.116516 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.233333 | false | 0 | 0 | 0 | 0.266667 | 0.133333 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
ec242099b667abe9316e5298f285dea3894ccdf1 | 478 | py | Python | facebook/modules/profile/user/admin.py | fabiangermann/django-facebook-graph | e63039c94a50f293ae79e8ecda24a9c7d1b61c68 | [
"Apache-2.0"
] | 1 | 2015-09-24T00:36:28.000Z | 2015-09-24T00:36:28.000Z | facebook/modules/profile/user/admin.py | fabiangermann/django-facebook-graph | e63039c94a50f293ae79e8ecda24a9c7d1b61c68 | [
"Apache-2.0"
] | null | null | null | facebook/modules/profile/user/admin.py | fabiangermann/django-facebook-graph | e63039c94a50f293ae79e8ecda24a9c7d1b61c68 | [
"Apache-2.0"
] | null | null | null | from django.contrib import admin
from facebook.modules.base import AdminBase
from .models import User
class UserAdmin(AdminBase):
list_display = ('id', 'profile_link', '_email', 'access_token', 'user', '_name', 'created', 'updated',)
readonly_fields = ('friends', '_name', '_locale', '_username', '_first_name', '_last_name', '_link', '_birthday', '_email', '_location', '_gender', '_graph')
search_fields = ('id', '_name')
admin.site.register(User, UserAdmin)
| 34.142857 | 161 | 0.694561 | 55 | 478 | 5.654545 | 0.690909 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.127615 | 478 | 13 | 162 | 36.769231 | 0.745803 | 0 | 0 | 0 | 0 | 0 | 0.320084 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.375 | 0 | 0.875 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 2 |
6b521d8e07f3cade2d1200e8918244586be7d2b6 | 721 | py | Python | kubeflow/utils/kaggle.py | GalaxyIT/kubeflow-utils | 911ef63df2e5b635960387390e7be397a293d83b | [
"Apache-2.0"
] | null | null | null | kubeflow/utils/kaggle.py | GalaxyIT/kubeflow-utils | 911ef63df2e5b635960387390e7be397a293d83b | [
"Apache-2.0"
] | null | null | null | kubeflow/utils/kaggle.py | GalaxyIT/kubeflow-utils | 911ef63df2e5b635960387390e7be397a293d83b | [
"Apache-2.0"
] | null | null | null | import json
from pathlib import Path
class Kaggle:
def login(self, username, apikey):
kaggle_json = Kaggle.__generate_kaggle_json_string(username, apikey)
Kaggle.__save_kaggle_json(kaggle_json)
@staticmethod
def __generate_kaggle_json_string(username, apikey):
data = {
"username": username,
"key": apikey
}
return json.dumps(data)
@staticmethod
def __save_kaggle_json(json_str):
kaggle_path = Path.home().joinpath('.kaggle')
if not kaggle_path.exists(): kaggle_path.mkdir(parents=True)
with open(str(kaggle_path.joinpath('kaggle.json')), 'w+') as kaggle_json:
print(json_str, file=kaggle_json)
| 27.730769 | 81 | 0.65742 | 86 | 721 | 5.186047 | 0.406977 | 0.201794 | 0.089686 | 0.107623 | 0.170404 | 0.170404 | 0 | 0 | 0 | 0 | 0 | 0 | 0.241331 | 721 | 25 | 82 | 28.84 | 0.815356 | 0 | 0 | 0.105263 | 1 | 0 | 0.042996 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.157895 | false | 0 | 0.105263 | 0 | 0.368421 | 0.052632 | 0 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
6b5ba2d44148c5c2ef3d2a547d1822bd946eb722 | 422 | py | Python | setup.py | panta/sample-n-files | dfa0928ec61e11b67ce15680478997e24dd00b64 | [
"Apache-2.0"
] | null | null | null | setup.py | panta/sample-n-files | dfa0928ec61e11b67ce15680478997e24dd00b64 | [
"Apache-2.0"
] | null | null | null | setup.py | panta/sample-n-files | dfa0928ec61e11b67ce15680478997e24dd00b64 | [
"Apache-2.0"
] | null | null | null | #!/usr/bin/env python
from setuptools import setup, find_packages
setup(
name="sample-n-files",
version="1.0",
author="Marco Pantaleoni",
description="Randomly sample N files from a directory.",
py_modules=['sample_n_files'],
install_requires=[
'Click'
],
entry_points='''
[console_scripts]
sample-n-files=sample_n_files:cli
''',
packages=find_packages()
)
| 21.1 | 60 | 0.64218 | 51 | 422 | 5.117647 | 0.666667 | 0.1341 | 0.229885 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.006098 | 0.222749 | 422 | 19 | 61 | 22.210526 | 0.789634 | 0.047393 | 0 | 0 | 0 | 0 | 0.413965 | 0.082294 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.0625 | 0 | 0.0625 | 0 | 0 | 0 | 0 | null | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
6b6aab5b1338487503c587746e4c1c1b8fcc7102 | 259 | py | Python | SoftLayer/fixtures/SoftLayer_Network_CdnMarketplace_Metrics.py | dvzrv/softlayer-python | 9a5f6c6981bcc370084537b4d1769383499ce90d | [
"MIT"
] | 126 | 2015-01-05T05:09:22.000Z | 2021-07-02T00:16:35.000Z | SoftLayer/fixtures/SoftLayer_Network_CdnMarketplace_Metrics.py | dvzrv/softlayer-python | 9a5f6c6981bcc370084537b4d1769383499ce90d | [
"MIT"
] | 969 | 2015-01-05T15:55:31.000Z | 2022-03-31T19:55:20.000Z | SoftLayer/fixtures/SoftLayer_Network_CdnMarketplace_Metrics.py | dvzrv/softlayer-python | 9a5f6c6981bcc370084537b4d1769383499ce90d | [
"MIT"
] | 176 | 2015-01-22T11:23:40.000Z | 2022-02-11T13:16:58.000Z | getMappingUsageMetrics = [
{
"names": [
"TotalBandwidth",
"TotalHits",
"HitRatio"
],
"totals": [
"0.0",
"0",
"0.0"
],
"type": "TOTALS"
}
]
| 16.1875 | 29 | 0.305019 | 13 | 259 | 6.076923 | 0.615385 | 0.101266 | 0.113924 | 0.101266 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.042017 | 0.540541 | 259 | 15 | 30 | 17.266667 | 0.621849 | 0 | 0 | 0.133333 | 0 | 0 | 0.227799 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
6b74c37ed0e549fee8d1a6b238cbee95f182541d | 210 | py | Python | src/utils/readfile/config.py | umimori13/mai-bot | 90e10f6488942809d4ca5ef342f403b683dbc904 | [
"MIT"
] | null | null | null | src/utils/readfile/config.py | umimori13/mai-bot | 90e10f6488942809d4ca5ef342f403b683dbc904 | [
"MIT"
] | null | null | null | src/utils/readfile/config.py | umimori13/mai-bot | 90e10f6488942809d4ca5ef342f403b683dbc904 | [
"MIT"
] | null | null | null | from pydantic import BaseSettings
class Config(BaseSettings):
# Your Config Here
dir_name = "src"
data_dir_name = "data"
config_dir_name = "config"
class Config:
extra = "ignore"
| 17.5 | 33 | 0.657143 | 25 | 210 | 5.32 | 0.56 | 0.157895 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.261905 | 210 | 11 | 34 | 19.090909 | 0.858065 | 0.07619 | 0 | 0 | 0 | 0 | 0.098958 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.142857 | 0 | 0.857143 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2 |
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